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arXiv 2024年

作者： Komędera, K. Siedliska, K. Gondek, L. Nalecz, D.M. Panek, R. Krupska-Klimczak, M. Jankowska-Sumara, I. Tokarz, W. Tabiś, W. Pikula, T. Faculty of Physics and Applied Computer Science AGH University of Krakow Mickiewicza 30 Kraków30-059 Poland Mössbauer Spectroscopy Laboratory University of National Education Commission Podchorążych 2 Kraków30-084 Poland Department of Electronics and Information Technologies Lublin University of Technology Nadbystrzycka 38A Lublin20-618 Poland Institute of Art and Design University of the National Education Commission Podchorążych 2 Kraków30-084 Poland Department of Construction Materials Engineering and Geoengineering Lublin University of Technology Nadbystrzycka 40 Lublin20-618 Poland Institute of Security Studies and Computer Science University of the National Education Commission Podchorążych 2 Kraków30-084 Poland Department of Exact and Natural Sciences University of the National Education Commission Podchorążych 2 Kraków30-084 Poland Institute of Solid State Physics TU Wien Vienna1040 Austria

In this study the structural and magnetic properties of Nd-doped BiFeO3 materials with the formula Bi1-xNdxFeO3 (x = 0–0.2) were investigated. Samples were prepared using the sol-gel method and annealed at 823 K for 4 hours. Microstructural studies indicated that nanomaterials with an average grain size of less than 100 nm were produced, with the smallest grain size observed for the solid solution with x = 0.15. Rietveld analysis of diffraction patterns revealed a composition-driven transformation from the rhombohedral (R3c) lattice to the orthorhombic (Pbam) structure. The above finding is correlated to Mössbauer spectroscopy data, which demonstrated the gradual destruction of the spin cycloid due to the structural transformation to the Pbam structure. The spectra were analyzed using a complex hyperfine magnetic field distribution model reflecting cycloidal spin ordering. Scanning differential calorimetry revealed that for the investigated materials the magnetic ordering temperatures are close to 640 K, independently from the Nd concentration. Magnetic measurements showed the emergence of weak ferromagnetic properties with increasing Nd ions concentration, consistently with Mössbauer spectroscopy data. © 2024, CC BY.

关键词： Sol-gel process

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ACHIEVING WELL-INFORMED DECISION-MAKING IN DRUG DISCOVERY: A COMPREHENSIVE CALIBRATION STUDY USING NEURAL NETWORK-BASED STRUCTURE-ACTIVITY MODELS

arXiv

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arXiv 2024年

作者： Friesacher, Hannah Rosa Engkvist, Ola Mervin, Lewis Moreau, Yves Arany, Adam ESAT STADIUS KU Leuven Leuven3000 Belgium Molecular AI Discovery Sciences R&D AstraZeneca Gothenburg Gothenburg 431 83 Sweden Molecular AI Discovery Sciences R&D AstraZeneca Cambridge CambridgeCB2 0AA United Kingdom Department of Computer Science and Engineering Chalmers University of Technology Gothenburg412 96 Sweden

In the drug discovery process, where experiments can be costly and time-consuming, computational models that predict drug-target interactions are valuable tools to accelerate the development of new therapeutic agents. Estimating the uncertainty inherent in these neural network predictions provides valuable information that facilitates optimal decision-making when risk assessment is crucial. However, such models can be poorly calibrated, which results in unreliable uncertainty estimates that do not reflect the true predictive uncertainty. In this study, we compare different metrics, including accuracy and calibration scores, used for model hyperparameter tuning to investigate which model selection strategy achieves well-calibrated models. Furthermore, we propose to use a computationally efficient Bayesian uncertainty estimation method named Bayesian Linear Probing (BLP), which generates Hamiltonian Monte Carlo (HMC) trajectories to obtain samples for the parameters of a Bayesian Logistic Regression fitted to the hidden layer of the baseline neural network. We report that BLP improves model calibration and achieves the performance of common uncertainty quantification methods by combining the benefits of uncertainty estimation and probability calibration methods. Finally, we show that combining post hoc calibration method with well-performing uncertainty quantification approaches can boost model accuracy and calibration. Copyright © 2024, The Authors. All rights reserved.

关键词： Risk assessment

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n-ary Isolation Forest: An Experimental Comparative Analysis 19th

n-ary Isolation Forest: An Experimental Comparative Analysis

引用

19th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2020

作者： Karczmarek, Pawel Kiersztyn, Adam Pedrycz, Witold Department of Computer Science Lublin University of Technology ul. Nadbystrzycka 36B Lublin20-618 Poland Department of Electrical and Computer Engineering University of Alberta EdmontonABT6R 2V4 Canada Department of Electrical and Computer Engineering Faculty of Engineering King Abdulaziz University Jeddah21589 Saudi Arabia Systems Research Institute Polish Academy of Sciences Warsaw Poland

ISBN: (纸本)9783030615338

One of the most challenging problems of modern data mining and Computational Intelligence society has been the task of anomaly detection in large datasets, particularly containing mixed data, namely categorical, spatial, or spatio-temporal. In this study, we discuss various versions of the well-known Isolation Forest method as a efficient tool for finding outliers or anomalies. The versions are based on binary, ternary, etc. search trees. Traditional Isolation Forest is based on searching binary search trees. We build and investigate n-ary search trees and analyze their efficiency in the context of anomaly detection. © 2020, Springer Nature Switzerland AG.

关键词： Anomaly detection

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Optically-Sampled Superconducting-Nanostrip Photon-Number Resolving Detector for Non-Classical Quantum State Generation

arXiv

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arXiv 2024年

作者： Endo, Mamoru Takahashi, Kazuma Nomura, Takefumi Sonoyama, Tatsuki Yabuno, Masahiro Miki, Shigehito Terai, Hirotaka Kashiwazaki, Takahiro Inoue, Asuka Umeki, Takeshi Nehra, Rajveer Takase, Kan Asavanant, Warit Furusawa, Akira Department of Applied Physics School of Engineering The University of Tokyo 7-3-1 Hongo Bunkyo Tokyo113-8656 Japan Optical Quantum Computing Research Team RIKEN Center for Quantum Computing 2-1 Hirosawa Saitama Wako351-0198 Japan Advanced ICT Research Institute National Institute of Information and Communications Technology 588-2 Iwaoka Nishi Kobe651-2492 Japan NTT Device Technology Labs NTT Corporation 3-1 Morinosato Wakamiya Kanagawa Atsugi243-0198 Japan Department of Electrical and Computer Engineering University of Massachusetts Amherst AmherstMA01003 United States Department of Physics University of Massachusetts Amherst AmherstMA01003 United States College of Information and Computer Science University of Massachusetts Amherst AmherstMA01003 United States

Photon number-resolving detectors (PNRDs) are the ultimate optical sensors. Superconducting-nanostrip photon detectors (SNSPDs), traditionally known as ON-OFF detectors, have recently been found to have photon number resolving capability without multiplexing. This discovery positions them to become true PNRDs. However, their practical use is limited by the need to precisely detect tiny signal differences with low signal-to-noise ratios within sub-nanosecond time frames. We overcome this challenge using optical sampling with a dual-output Mach Zehnder modulator (DO-MZM) and ultra-short pulsed laser. By adjusting the DO-MZM’s bias voltage to nearly balance the outputs, this method enables sensitive detection of picosecond-order signal differences, achieving a temporal resolution of 1.9 ps and facilitating real-time photon number resolution. We applied this method to produce various non-classical quantum states, enhancing their non-classicality through photon number resolution. This advancement marks a significant shift from principle verification to practical application for SNSPD-type PNRDs in diverse quantum optics fields. Copyright © 2024, The Authors. All rights reserved.

关键词： Quantum optics

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Low-resolution human pose estimation

arXiv

引用

arXiv 2021年

作者： Wang, Chen Zhang, Feng Zhu, Xiatian Ge, Shuzhi Sam School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China School of Computer Science and Technology Nanjing University of Posts and Telecommunications Nanjing China Centre for Vision Speech and Signal Processing Faculty of Engineering and Physical Sciences University of Surrey GuildfordGU2 7XH United Kingdom Department of Electrical and Computer Engineering National University of Singapore Singapore Singapore

Human pose estimation has achieved significant progress on images with high imaging resolution. However, low-resolution imagery data bring nontrivial challenges which are still under-studied. To fill this gap, we start with investigating existing methods and reveal that the most dominant heatmap-based methods would suffer more severe model performance degradation from low-resolution, and offset learning is an effective strategy. Established on this observation, in this work we propose a novel Confidence-Aware Learning (CAL) method which further addresses two fundamental limitations of existing offset learning methods: inconsistent training and testing, decoupled heatmap and offset learning. Specifically, CAL selectively weighs the learning of heatmap and offset with respect to ground-truth and most confident prediction, whilst capturing the statistical importance of model output in mini-batch learning manner. Extensive experiments conducted on the COCO benchmark show that our method outperforms significantly the state-of-the-art methods for low-resolution human pose estimation. © 2021, CC BY-SA.

关键词： Learning systems

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Cybersecurity Threats in FinTech: A Systematic Review

arXiv

引用

arXiv 2023年

作者： Javaheri, Danial Fahmideh, Mahdi Chizari, Hassan Lalbakhsh, Pooia Hur, Junbeom Department of Computer Science and Engineering Korea University Seoul02841 Korea Republic of School of Business University of Southern Queensland SpringfieldQLD4300 Australia School of Business Computing and Social Sciences University of Gloucestershire The Park CampusCheltenham GloucesterGL50 2RH United Kingdom Department of Data Science and Artificial Intelligence Faculty of Information Technology Monash University ClaytonVIC3168 Australia

The rapid evolution of the Smart-everything movement and Artificial Intelligence (AI) advancements have given rise to sophisticated cyber threats that traditional methods cannot counteract. Cyber threats are extremely critical in financial technology (FinTech) as a data-centric sector expected to provide 24/7 services. This paper introduces a novel and refined taxonomy of security threats in FinTech and conducts a comprehensive systematic review of defensive strategies. Through PRISMA methodology applied to 74 selected studies and topic modeling, we identified 11 central cyber threats, with 43 papers detailing them, and pinpointed 9 corresponding defense strategies, as covered in 31 papers. This in-depth analysis offers invaluable insights for stakeholders ranging from banks and enterprises to global governmental bodies, highlighting both the current challenges in FinTech and effective countermeasures, as well as directions for future research. © 2023, CC BY.

关键词： Cybersecurity

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An ensemble deep learning model for predicting minimum inhibitory concentrations of antimicrobial peptides against pathogenic bacteria

引用

iscience 2024年第9期27卷

作者： Chung, Chia-Ru Chien, Chung-Yu Tang, Yun Wu, Li-Ching Hsu, Justin Bo-Kai Lu, Jang-Jih Lee, Tzong-Yi Bai, Chen Horng, Jorng-Tzong Department of Computer Science and Information Engineering National Central University Taoyuan Taiwan Institute of Bioinformatics and Systems Biology National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Biomedical Sciences and Engineering National Central University Taoyuan Taiwan Department of Computer Science and Engineering Yuan Ze University Taoyuan Taiwan Department of Laboratory Medicine Chang Gung Memorial Hospital at Linkou Taoyuan City Taiwan School of Medicine Chang Gung University Taoyuan City Taiwan Department of Medical Biotechnology and Laboratory Science Chang Gung University Taoyuan City Taiwan Center for Intelligent Drug Systems and Smart Biodevices (IDS2B) National Yang Ming Chiao Tung University Hsinchu City Taiwan Warshel Institute for Computational Biology School of Medicine The Chinese University of Hong Kong (Shenzhen) Shenzhen 518172 Hong Kong

The rise of antibiotic resistance necessitates effective alternative therapies. Antimicrobial peptides (AMPs) are promising due to their broad inhibitory effects. This study focuses on predicting the minimum inhibitory concentration (MIC) of AMPs against whom-priority pathogens: Staphylococcus aureus ATCC 25923, Escherichia coli ATCC 25922, and Pseudomonas aeruginosa ATCC 27853. We developed a comprehensive regression model integrating AMP sequence-based and genomic features. Using eight AI-based architectures, including deep learning with protein language model embeddings, we created an ensemble model combining bi-directional long short-term memory (BiLSTM), convolutional neural network (CNN), and multi-branch model (MBM). The ensemble model showed superior performance with Pearson correlation coefficients of 0.756, 0.781, and 0.802 for the bacterial strains, demonstrating its accuracy in predicting MIC values. This work sets a foundation for future studies to enhance model performance and advance AMP applications in combating antibiotic resistance. © 2024 The Authors

关键词： Biological sciences Chemistry computer science

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Distributed Approach to Traffic Management Automation Implemented According to IEC 61499 11th

Distributed Approach to Traffic Management Automation Implem...

引用

11th Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2020

作者： Elkin, Dmitry Vyatkin, Valeriy Institute of Computer Technologies and Information Security Southern Federal University Chekhova. 2 Taganrog347900 Russia Department of Electrical Engineering and Automation Aalto University Otakaari 1B Aalto00076 Finland Department of Computer Science Electrical and Space Engineering Luleå University of Technology Luleå97187 Sweden

ISBN: (纸本)9783030451233

The number of vehicles on public roads is increasing while the road infrastructure is not keeping up to this. It is necessary to apply advanced algorithms and approaches to transport management to maximize the use of the existing road network and increase the capacity of roads. In this article, we propose a way to control traffic flows and automate road infrastructure using a multi-agent approach. The proposed approach involves the distributed management of various elements on the road network and their direct relationship with each other in a peer to peer manner. To implement this concept, we used the open standard of distributed control and automation systems IEC 61499, and to validate the approach we used the SUMO - microscopic and continuous road traffic simulation package. © IFIP International Federation for Information Processing 2020.

关键词： Multi agent systems

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PELE scores: Pelvic X-ray Landmark Detection by Pelvis Extraction and Enhancement

arXiv

引用

arXiv 2023年

作者： Huang, Zhen Li, Han Shao, Shitong Zhu, Heqin Hu, Huijie Cheng, Zhiwei Wang, Jianji Zhou, S. Kevin Computer Science Department University of Science and Technology of China Hefei230026 China School of Biomedical Engineering Suzhou Institute for Advanced Research University of Science and Technology of China Suzhou215123 China Southeast University Nanjing China Institute of Computing Technology CAS Beijing100190 China Z2Sky Technologies Inc. Suzhou215123 China Affiliated Hospital of Guizhou Medical University Guiyang550000 China

The pelvis, the lower part of the trunk, supports and balances the trunk. Landmark detection from a pelvic X-ray (PXR) facilitates downstream analysis and computer-assisted diagnosis and treatment of pelvic diseases. Although PXRs have the advantages of low radiation and reduced cost compared to computed tomography (CT) images, their 2D pelvis-tissue superposition of 3D structures confuses clinical decision-making. In this paper, we propose a PELvis Extraction (PELE) module that utilizes 3D prior anatomical knowledge in CT to guide and well isolate the pelvis from PXRs, thereby eliminating the influence of soft tissue. We conduct an extensive evaluation based on two public datasets and one private dataset, totaling 850 PXRs. The experimental results show that the proposed PELE module significantly improves the accuracy of PXRs landmark detection and achieves state-of-the-art performances in several benchmark metrics, thus better serving downstream tasks. Copyright © 2023, The Authors. All rights reserved.

关键词： Extraction

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Improved MDL Estimators Using Fiber Bundle of Local Exponential Families for Non-exponential Families

arXiv

引用

arXiv 2023年

作者： Miyamoto, Kohei Barron, Andrew R. Takeuchi, Jun'ichi Cybersecurity Laboratory Cybersecurity Research Institute National Institute of Information and Communications Technology 4-2-1 Nukui-Kitamachi Koganei Tokyo184-8795 Japan Department of Statistics and Data Science Yale University Kline Tower 219 Prospect Street New HavenCT06511 United States Department of Electrical Engineering and Computer Science Kyushu University 744 Motooka Nishi-ku Fukuoka Fukuoka819-0395 Japan

Minimum Description Length (MDL) estimators, using two-part codes for universal coding, are analyzed. For general parametric families under certain regularity conditions, we introduce a two-part code whose regret is close to the minimax regret, where regret of a code with respect to a target family M is the difference between the code length of the code and the ideal code length achieved by an element in M. This is a generalization of the result for exponential families by Grünwald. Our code is constructed by using an augmented structure of M with a bundle of local exponential families for data description, which is not needed for exponential families. This result gives a tight upper bound on risk and loss of the MDL estimators based on the theory introduced by Barron and Cover in 1991. Further, we show that we can apply the result to mixture families, which are a typical example of non-exponential families. Copyright © 2023, The Authors. All rights reserved.

关键词： Data description

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