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Resource engines

arXiv 2023年

作者： Wojewódka-Ściążko, Hanna Puchala, Zbigniew Korzekwa, Kamil Institute of Mathematics University of Silesia in Katowice Bankowa 14 Katowice40-007 Poland Institute of Theoretical and Applied Informatics Polish Academy of Sciences Baltycka 5 Gliwice44-100 Poland Faculty of Physics Astronomy and Applied Computer Science Jagiellonian University Kraków30-348 Poland

In this paper we aim to push the analogy between thermodynamics and quantum resource theories one step further. Previous inspirations were based predominantly on thermodynamic considerations concerning scenarios with a single heat bath, neglecting an important part of thermodynamics that studies heat engines operating between two baths at different temperatures. Here, we investigate the performance of resource engines, which replace the access to two heat baths at different temperatures with two arbitrary constraints on state transformations. The idea is to imitate the action of a two-stroke heat engine, where the system is sent to two agents (Alice and Bob) in turns, and they can transform it using their constrained sets of free operations. We raise and address several questions, including whether or not a resource engine can generate a full set of quantum operations or all possible state transformations, and how many strokes are needed for that. We also explain how the resource engine picture provides a natural way to fuse two or more resource theories, and we discuss in detail the fusion of two resource theories of thermodynamics with two different temperatures, and two resource theories of coherence with respect to two different bases. © 2023, CC BY.

关键词： Temperature

Work-in-Progress: Using the PerFECt Framework to Design and Implement Blended Learning Activities to Introduce the Binary System in Primary School Students

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Work-in-Progress: Using the PerFECt Framework to Design and ...

9th International Conference on Interactive Collaborative and Blended Learning, ICBL 2020

作者： Moumoutzis, Nektarios Rigas, Nikolaos Apostolos Xanthaki, Chara Maragkoudakis, Yiannis Christodoulakis, Christina Paneva-Marinova, Desislava Pavlova, Lilia Laboratory of Distributed Multimedia Information Systems and Applications School of Electrical and Computer Engineering Technical University of Crete Chania Crete73100 Greece Institute of Mathematics and Informatics Bulgarian Academy of Sciences Sofia1113 Bulgaria Directorate of Secondary Education Chania Crete Greece Department of Computer Science University of Toronto Toronto Canada Laboratory of Telematics Bulgarian Academy of Sciences Sofia1113 Bulgaria

ISBN: (纸本)9783030672089

This paper presents how the PerFECt framework is employed to enable innovative teaching and learning mathematics in schools using drama-based approaches. The topic addressed lies in the cross-section between mathematics and computer science: teaching and learning the binary system of arithmetic that constitutes the basis of modern computing. The work builds on previous research efforts targeting gamification of mathematics and is seen under new light offered by the Theatre in Mathematics (TIM) Methodology. The result is an engaging game to teach the binary system to children using their bodies and simple rules for interacting with each other. Following these simple rules the participants enact the operation of a calculator that is able to transform integers into their binary representations and compute the result of the four arithmetic operations (addition, subtraction, multiplication and division). The game can be combined with online activities using a simulator of the game, so that learners can explore it for themselves and discover how the arithmetic operations are done, even when they are not in the same physical space with their peers. This way, an effective blended learning approach is ultimately offered combining face-to-face and online activities. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Learning systems

DSP Filter Kernels Preliminary Benchmarking for Recurrent Data-flow Architecture

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DSP Filter Kernels Preliminary Benchmarking for Recurrent Da...

IEEE NW Russia Young Researchers in Electrical and Electronic Engineering Conference (EIConRusNW)

作者： Yury A. Stepchenkov Dmitry V. Khilko Yury I. Shikunov Georgy A. Orlov Institute of Informatics Problems Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences (FRC CSC RAS) Moscow Russia

ISBN: (数字)9781665404761

ISBN: (纸本)9781665446426

The article discusses the results of a preliminary assessment of the data-flow recurrent architecture's performance on a subset of digital signal processing key tasks. Various implementations of vector convolution, FIR filters, IIR filters, adaptive filter, and 256-Point-In-Place FFT are evaluated. The implementation of the listed algorithms is based on the TMS320C55x DSP Library. The preliminary results showed that the performance of the recurrent architecture based on data-flow principles is not inferior to the TMS320C55x, based on von Neumann principles, in terms of the number of computation cycles. Architecture improvement suggestions are presented.

关键词： Finite impulse response filters computer architecture IIR filters Benchmark testing Libraries Kernel Task analysis

The sum of entanglement and subsystem coherence is invariant under quantum reference frame transformations

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arXiv 2024年

作者： Cepollaro, Carlo Akil, Ali Cieśliński, Pawel de la Hamette, Anne-Catherine Brukner, Časlav Faculty of Physics University of Vienna Boltzmanngasse 5 ViennaA-1090 Austria Austrian Academy of Sciences Boltzmanngasse 3 ViennaA-1090 Austria Department of Computer Science The University of Hong Kong Hong Kong Island Hong Kong Institute of Theoretical Physics and Astrophysics Faculty of Mathematics Physics and Informatics University of Gdańsk Gdańsk80-308 Poland

Recent work on quantum reference frames (QRFs) has demonstrated that superposition and entanglement are properties that change under QRF transformations. Given their utility in quantum information processing, it is important to understand how a mere change of perspective can produce or reduce these resources. Here we find a trade-off between entanglement and subsystem coherence under a QRF transformation, in the form of a conservation theorem for their sum, for two pairs of measures. Moreover, we find a weaker trade-off for any possible pair of measures. Finally, we discuss the implications of this interplay for violations of Bell's inequalities, clarifying that for any choice of QRF, there is a quantum resource responsible for the violation. These findings contribute to a better understanding of the quantum information theoretic aspects of QRFs, offering a foundation for future exploration in both quantum theory and quantum gravity. © 2024, CC BY.

关键词： Quantum entanglement

MassSpecGym: A benchmark for the discovery and identification of molecules

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arXiv 2024年

作者： Bushuiev, Roman Bushuiev, Anton de Jonge, Niek F. Young, Adamo Kretschmer, Fleming Samusevich, Raman Heirman, Janne Wang, Fei Zhang, Luke Dührkop, Kai Ludwig, Marcus Haupt, Nils A. Kalia, Apurva Brungs, Corinna Schmid, Robin Greiner, Russell Wang, Bo Wishart, David S. Liu, Li-Ping Rousu, Juho Bittremieux, Wout Rost, Hannes Mak, Tytus D. Hassoun, Soha Huber, Florian van der Hooft, Justin J.J. Stravs, Michael A. Böcker, Sebastian Sivic, Josef Pluskal, Tomáš Institute of Organic Chemistry and Biochemistry The Czech Academy of Sciences Czech Republic Czech Institute of Informatics Robotics and Cybernetics Czech Technical University Czech Republic Bioinformatics Group Wageningen University & Research Netherlands Department of Computer Science University of Toronto Canada Institute for Computer Science Friedrich Schiller University Jena Germany Department of Computer Science University of Antwerp Belgium Department of Computing Science University of Alberta Canada Alberta Machine Intelligence Institute Canada Department of Molecular Genetics University of Toronto Canada Bright Giant GmbH Germany Department of Computer Science Tufts University United States Department of Biological Sciences University of Alberta Canada Department of Computer Science Aalto University Finland Mass Spectrometry Data Center National Institute of Standards and Technology United States Department of Chemical and Biological Engineering Tufts University United States Centre for Digitalisation and Digitality University of Applied Sciences Düsseldorf Germany Department of Biochemistry University of Johannesburg South Africa Eawag: Swiss Federal Institute of Aquatic Science and Technology Switzerland

The discovery and identification of molecules in biological and environmental samples is crucial for advancing biomedical and chemical sciences. Tandem mass spectrometry (MS/MS) is the leading technique for high-throughput elucidation of molecular structures. However, decoding a molecular structure from its mass spectrum is exceptionally challenging, even when performed by human experts. As a result, the vast majority of acquired MS/MS spectra remain uninterpreted, thereby limiting our understanding of the underlying (bio)chemical processes. Despite decades of progress in machine learning applications for predicting molecular structures from MS/MS spectra, the development of new methods is severely hindered by the lack of standard datasets and evaluation protocols. To address this problem, we propose MassSpecGym – the first comprehensive benchmark for the discovery and identification of molecules from MS/MS data. Our benchmark comprises the largest publicly available collection of high-quality labeled MS/MS spectra and defines three MS/MS annotation challenges: de novo molecular structure generation, molecule retrieval, and spectrum simulation. It includes new evaluation metrics and a generalization-demanding data split, therefore standardizing the MS/MS annotation tasks and rendering the problem accessible to the broad machine learning community. MassSpecGym is publicly available at https://***/pluskal-lab/MassSpecGym. Copyright © 2024, The Authors. All rights reserved.

关键词： Benchmarking

Generation of Dynamic Authorization Using Cryptography For Private-Keyless Data Sharing

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SSRN

SSRN 2023年

作者： Lu, Hai Zhu, Yan Yau, Stephen S. Zhu, Guizhen Lv, Kewei School of Computer and Communication Engineering University of Science and Technology Beijing Beijing100083 China School of Computing Informatics and Decision Systems Engineering Arizona State University TempeAZ85281 United States Data and Communication Science Technology Research Institute Beijing100191 China School of Cyber Security University of Chinese Academy of Sciences Beijing100093 China

Private-keyless access is emerging as an inevitable trend in the evolution of future information systems. It helps simplify key management, enhance security, and increase flexibility of access authorization. Hereby, we introduce a novel security model, Cryptographic Resource Enabled Infrastructure (CREI), to support private-keyless access and policy-based data custody. Firstly, in the data custody phase, data resource and its session key are uploaded in ciphertext form to CREI, and the access authorization complies with multiple policies designated by the provider. Secondly, in the dynamic authorization phase, traditional keys or keycards are replaced with real-time attribute credentials issued by multiple authorities. CREI makes dynamically cryptographic policy decision according to the credentials and the cryptographic policy (cryptopolicy). Technically, we design the Credentials-Driven Cryptosystem (CDC) over ideal lattice to build anti-quantum confidence for CREI. In CDC, preimage Gaussian sampler is adopted to sample short vector as real-time attribute credential instead of user's private key. Small Policy Matrix (SPM) is implemented to convert monotone policies into optimized cryptopolicies in order to reduce accumulated error. The security analysis confirms that the credentials, cryptopolicy and its decision result are existentially unforgeable, ensuring the semantic security of the whole CREI. Experimental results indicate CREI has lower storage and computational costs than existing schemes. Meanwhile, despite continuous improvements to the access policies as system evolves, CREI can simply select an appropriate policy among multiple candidates to make authorization decisions without having to re-encrypt data. © 2023, The Authors. All rights reserved.

关键词： Authorization

Comparing Different Membership Inference Attacks with a Comprehensive Benchmark

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IEEE Transactions on Information Forensics and Security 2025年

作者： Niu, Jun Zhu, Xiaoyan Zeng, Moxuan Zhang, Ge Zhao, Qingyang Huang, Chunhui Zhang, Yangming An, Suyu Wang, Yangzhong Yue, Xinghui He, Zhipeng Guo, Weihao Shen, Kuo Liu, Peng Zhang, Lan Ma, Jianfeng Zhang, Yuqing Xidian University School of Cyber Engineering School of Computer Science and Technology Xi'an710071 China Xidian University School of Telecommunications Engineering Xi'an710071 China Xidian University School of Hangzhou Institute of Technology Hangzhou311231 China Pennsylvania State University Information Sciences and Technology 16802 United States Northern Arizona University The School of Informatics Computing & Cyber Systems FlagstaffAZ86005 United States Xidian University School of Cyber Engineering Xi'an710071 China Yanshan University The College of Information Science and Engineering Qinhuangdao066004 China University of Chinese Academy of Sciences The School of Computer Science and Technology Beijing101408 China The School of Cyberspace Security Hainan University Haikou570228 China

Membership inference (MI) attacks pose a significant threat to user privacy in machine learning. While numerous attacks have been proposed, the lack of standardized evaluation parameters and metrics has led to inconsistent and even conflicting comparison results. To address this issue and facilitate a systematic analysis of these disparate findings, we introduce MIBench, a comprehensive benchmark that includes a suite of carefully designed evaluation scenarios (ESs) and evaluation metrics to provide a consistent framework for assessing various MI techniques. The ESs are crafted to encompass four critical factors: intra-dataset distance distribution, inter-sample distance within the target dataset, differential distance analysis, and inference withholding ratio. MIBench includes ten typical evaluation metrics and 84 distinct ESs per dataset. Using MIBench, we conducted a thorough comparative analysis of 15 state-of-the-art MI attacks across 588 ESs, seven widely adopted datasets, and seven representative model architectures. Our analysis revealed 83 instances of Conflicting Comparison Results (CCR), providing substantial evidence for the CCR Phenomenon. We identified two CCR types: Type 1 (single-factor) and Type 2 (dual-factor). The CCR distribution across four factors was: inter-sample distance (40.96%), differential distance (37.35%), inference withholding ratio (19.28%), and intra-dataset distance (2.41%). All MIBench codes and evaluations are available at link. © 2025 IEEE.

关键词： Differential privacy

eShadow+: Mixed Reality Storytelling Inspired by Traditional Shadow Theatre

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eShadow+: Mixed Reality Storytelling Inspired by Traditional...

IEEE Annual International computer Software and Applications Conference (COMPSAC)

作者： Nektarios Moumoutzis Marios Christoulakis Chara Xanthaki Yiannis Maragoudakis Stavros Christodoulakis Desislava Paneva-Marinova Lilia Pavlova Bulgarian Academy of Sciences Institute of Mathematics and Informatics Sofia Bulgaria Lab. of Distr. Multimedia Inf. Systems &#x0026 Applications School of Electrical &#x0026 Computer Eng. Technical University of Crete Chania Greece Computer Science Teacher Directorate of Secondary Education Chania Greece Laboratory of Telematics Bulgarian Academy of Sciences Sofia Bulgaria

ISBN: (数字)9781665488105

ISBN: (纸本)9781665488112

eShadow is a digital storytelling platform inspired by traditional Shadow Theatre. It enables the creation of digital stories within a project-based approach that may start from scenario development and include the creation of digital puppets and sceneries, the set-up and recording of story scenes and the final assembly of a digital story. This paper presents how eShadow can be enhanced to solve the problem of creating mixed reality installations to offer rich learning experiences in informal learning settings. This enhanced version is eShadow+ and it is evaluated via two installations which are described and compared. The evaluation results demonstrate the effectiveness of the approach thus offering new learning opportunities that are aligned with current trends in the use of mixed reality technologies.

关键词： Conferences Mixed reality Market research Software Recording

A Hierarchical Interactive Network for Joint Span-based Aspect-Sentiment Analysis

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arXiv 2022年

作者： Chen, Wei Du, Jinglong Zhang, Zhao Zhuang, Fuzhen He, Zhongshi College of Computer Science Chongqing University Chongqing China Institute of Artificial Intelligence Beihang University Beijing100191 China College of Medical Informatics Chongqing Medical University Chongqing China Institute of Computing Technology Chinese Academy of Sciences Beijing China SKLSDE School of Computer Science Beihang University Beijing100191 China

Recently, some span-based methods have achieved encouraging performances for joint aspect-sentiment analysis, which first extract aspects (aspect extraction) by detecting aspect boundaries and then classify the span-level sentiments (sentiment classification). However, most existing approaches either sequentially extract task-specific features, leading to insufficient feature interactions, or they encode aspect features and sentiment features in a parallel manner, implying that feature representation in each task is largely independent of each other except for input sharing. Both of them ignore the internal correlations between the aspect extraction and sentiment classification. To solve this problem, we novelly propose a hierarchical interactive network (HI-ASA) to model two-way interactions between two tasks appropriately, where the hierarchical interactions involve two steps: shallow-level interaction and deep-level interaction. First, we utilize cross-stitch mechanism to combine the different task-specific features selectively as the input to ensure proper two-way interactions. Second, the mutual information technique is applied to mutually constrain learning between two tasks in the output layer, thus the aspect input and the sentiment input are capable of encoding features of the other task via backpropagation. Extensive experiments on three real-world datasets demonstrate HI-ASA’s superiority over baselines1 © 2022, CC BY.

关键词： Sentiment analysis