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IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： Vasileios Kouvakis Stylianos E. Trevlakis Alexandros-Apostolos A. Boulogeorgos Theodoros Tsiftsis Keshav Singh Nan Qi Department of Research and Development InnoCube P.C. 17th Noemvriou 79 Thessaloniki Greece Department of Electrical and Computer Engineering University of Western Macedonia Kozani Greece Department of Informatics & Telecommunications University of Thessaly Lamia Greece Institute of Communications Engineering National Sun Yat-sen University Kaohsiung Taiwan Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Nanjing University of Aeronautics and Astronautics Nanjing China

ISBN: (数字)9798350362244

ISBN: (纸本)9798350362251

This paper presents an American sign language (ASL) semantic communications scheme. The scheme consists of a semantic encoder that leverages a convolutional neural network to effectively utilize the ASL alphabet. The encoded information is transmitted with the 24-QAM quadrature amplitude modulation (QAM). Additionally, this paper introduces a dataset that involves the overlaying of red-green-blue landmarks and key-points onto the acquired images, thereby augmenting the depiction of hand posture. The quantification of the proposed system’s training, testing, and communication performance is accomplished through numerical results, which serve to emphasize the attainable benefits and stimulate meaningful discussions.

关键词： Training Hands Sign language Quadrature amplitude modulation Assistive technologies Semantic communication Numerical models Convolutional neural networks Testing Land mobile radio

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Recording provenance of workflow runs with RO-Crate

arXiv

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arXiv 2023年

作者： Leo, Simone Crusoe, Michael R. Rodríguez-Navas, Laura Sirvent, Raül Kanitz, Alexander De Geest, Paul Wittner, Rudolf Pireddu, Luca Garijo, Daniel Fernández, José M. Colonnelli, Iacopo Gallo, Matej Ohta, Tazro Suetake, Hirotaka Capella-Gutierrez, Salvador de Wit, Renske Kinoshita, Bruno P. Soiland-Reyes, Stian CA Pula Italy Vrije Universiteit Amsterdam Amsterdam Netherlands DTL Projects Netherlands Forschungszentrum Jülich Germany Barcelona Supercomputing Center Barcelona Spain Biozentrum University of Basel Basel Switzerland Swiss Institute of Bioinformatics Lausanne Switzerland VIB Data Core Gent Belgium Faculty of Informatics Masaryk University Brno Czech Republic Institute of Computer Science Masaryk University Brno Czech Republic BBMRI-ERIC Graz Austria Ontology Engineering Group Universidad Politécnica de Madrid Madrid Spain Computer Science Department Università degli Studi di Torino Torino Italy Database Center for Life Science Joint Support-Center for Data Science Research Research Organization of Information and Systems Shizuoka Japan Institute for Advanced Academic Research Chiba University Chiba Japan Sator Incorporated Tokyo Japan Department of Computer Science The University of Manchester Manchester United Kingdom Informatics Institute University of Amsterdam Amsterdam Netherlands

Recording the provenance of scientific computation results is key to the support of traceability, reproducibility and quality assessment of data products. Several data models have been explored to address this need, providing representations of workflow plans and their executions as well as means of packaging the resulting information for archiving and sharing. However, existing approaches tend to lack interoperable adoption across workflow management systems. In this work we present Workflow Run RO-Crate, an extension of RO-Crate (research Object Crate) and *** to capture the provenance of the execution of computational workflows at different levels of granularity and bundle together all their associated objects (inputs, outputs, code, etc.). The model is supported by a diverse, open community that runs regular meetings, discussing development, maintenance and adoption aspects. Workflow Run RO-Crate is already implemented by several workflow management systems, allowing interoperable comparisons between workflow runs from heterogeneous systems. We describe the model, its alignment to standards such as W3C PROV, and its implementation in six workflow systems. Finally, we illustrate the application of Workflow Run RO-Crate in two use cases of machine learning in the digital image analysis domain. © 2023, CC BY.

关键词： Workflow management

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Trusted Execution Environments for Cloud/Fog-based Internet of Things Applications 11

Trusted Execution Environments for Cloud/Fog-based Internet ...

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11th International Conference on Cloud Computing and Services Science, CLOSER 2021

作者： Valadares, Dalton Cézane Gomes Will, Newton Carlos Spohn, Marco Aurélio Santos, Danilo Freire de Souza Perkusich, Angelo Gorgonio, Kyller Costa Federal Institute of Pernambuco Mechanical Engineering Department PE Caruaru Brazil Federal University of Campina Grande Informatics and Electrical Engineering Center Computer Science PB Campina Grande Brazil Federal University of Technology - Paraná PR Dois Vizinhos Brazil Federal University of Fronteira Sul SC Chapecó Brazil

ISBN: (纸本)9789897585104

Cloud services and fog-based solutions can improve the communication and processing efficiency of the Internet of Things (IoT). Cloud and fog servers offer more processing power to IoT solutions, enabling more complex tasks within reduced time frames, which could not be possible when relying solely on IoT devices. Cloud and fog computing benefits are even better when considering sensitive data processing once IoT devices can hardly perform complex security tasks. To improve data security in cloud/fog-based IoT solutions, Trusted Execution Environments (TEEs) allow the processing of sensitive data and code inside protected and isolated regions of memory. This paper presents a brief survey regarding TEEs’ adoption to protect data in cloud/fog-based IoT applications. We focus on solutions based on the two leading TEE technologies currently available in the market (Intel SGX and ARM Trustzone), pointing out some research challenges and directions. Copyright © 2021 by SCITEPRESS – Science and technology Publications, Lda. All rights reserved

关键词： Internet of things

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Clifford circuit based heuristic optimization of fermion-to-qubit mappings

arXiv

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arXiv 2025年

作者： Yu, Jeffery Liu, Yuan Sugiura, Sho Van Voorhis, Troy Zeytinŏglu, Sina Joint Center for Quantum Information and Computer Science NIST University of Maryland College ParkMD20742 United States Joint Quantum Institute NIST University of Maryland College ParkMD20742 United States Department of Electrical and Computer Engineering North Carolina State University RaleighNC27606 United States Department of Computer Science North Carolina State University RaleighNC27606 United States Department of Physics North Carolina State University RaleighNC27606 United States Blocq Inc. 717 Market Street San FranciscoCA94103 United States Department of Chemistry Massachusetts Institute of Technology CambridgeMA02139 United States Institute for Theoretical Physics TU Wien Wiedner Hauptstraße 8-10/136 ViennaA-1040 Austria Physics and Informatics Laboratory NTT Research Inc. SunnyvaleCA94085 United States

Simulation of interacting fermionic Hamiltonians is one of the most promising applications of quantum computers. However, the feasibility of analysing fermionic systems with a quantum computer hinges on the efficiency of fermion-to-qubit mappings that encode non-local fermionic degrees of freedom in local qubit degrees of freedom. While recent works have highlighted the importance of designing fermion-to-qubit mappings that are tailored to specific problem Hamiltonians, the methods proposed so far are either restricted to a narrow class of mappings or they use computationally expensive and unscalable brute-force search algorithms. Here, we address this challenge by designing a heuristic numerical optimization framework for fermion-to-qubit mappings. To this end, we first translate the fermion-to-qubit mapping problem to a Clifford circuit optimization problem, and then use simulated annealing to optimize the average Pauli weight of the problem Hamiltonian. For all fermionic Hamiltonians we have considered, the numerically optimized mappings outperform their conventional counterparts, including ternary-tree-based mappings that are known to be optimal for single creation and annihilation operators. We find that our optimized mappings yield between 15% to 40% improvements on the average Pauli weight when the simulation Hamiltonian has an intermediate level of complexity. Most remarkably, the optimized mappings improve the average Pauli weight for 6×6 nearest-neighbor hopping and Hubbard models by more than 40% and 20%, respectively. Surprisingly, we also find specific interaction Hamiltonians for which the optimized mapping outperform any ternary-tree-based mapping. Our results establish heuristic numerical optimization as an effective method for obtaining mappings tailored for specific fermionic Hamiltonian. © 2025, CC BY.

关键词： Hamiltonians

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On the Effectiveness of Binary Emulation in Malware Classification

arXiv

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arXiv 2022年

作者： Vouvoutsis, Vasilis Casino, Fran Patsakis, Constantinos Department of Informatics University of Piraeus 80 Karaoli & Dimitriou str. Piraeus18534 Greece Department of Computer Engineering and Mathematics Universitat Rovira i Virgili Spain Information Management Systems Institute Athena Research Centre Greece

Malware authors are continuously evolving their code base to include counter-analysis methods that can significantly hinder their detection and blocking. While the execution of malware in a sandboxed environment may provide a lot of insightful feedback about what the malware actually does in a machine, anti-virtualisation and hooking evasion methods may allow malware to bypass such detection methods. The main objective of this work is to complement sandbox execution with the use of binary emulation frameworks. The core idea is to exploit the fact that binary emulation frameworks may quickly test samples quicker than a sandbox environment as they do not need to open a whole new virtual machine to execute the binary. While with this approach, we lose the granularity of the data that can be collected through a sandbox, due to scalability issues, one may need to simply determine whether a file is malicious or to which malware family it belongs. To this end, we record the API calls that are performed and use them to explore the efficacy of using them as features for binary and multiclass classification. Our extensive experiments with real-world malware illustrate that this approach is very accurate, achieving state-of-the art outcomes with a statistically robust set of classification experiments while simultaneously having a relatively low computational overhead compared to traditional sandbox approaches. In fact, we compare the binary analysis results with a commercial sandbox, and our classification outperforms it at the expense of the fine-grained results that a sandbox provides. Copyright © 2022, The Authors. All rights reserved.

关键词： Malware

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Towards Narrowing the Search in Bounded-Suboptimal Safe Interval Path Planning 14

Towards Narrowing the Search in Bounded-Suboptimal Safe Inte...

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14th International Symposium on Combinatorial Search, SoCS 2021

作者： Rybecky, Tomas Kulich, Miroslav Andreychuk, Anton Yakovlev, Konstantin Department of Cybernetics Faculty of Electrical Engineering Czech Technical University Czech Republic Czech Institute for Informatics Robotics and Cybernetics Czech Technical University Czech Republic Federal Research Center for Computer Science and Control of Russian Academy of Sciences Russia Russia National Research University Higher School of Economics Russia

ISBN: (纸本)9781713834557

Path planning in the presence of dynamic obstacles is challenging as the time dimension has to be considered. A prominent approach to tackle this problem known to be complete and optimal is the A*-based Safe-interval Path Planning (SIPP). Bounded-suboptimal variants of SIPP employing the ideas of Weighted A* (WSIPP) and Focal Search (FocalSIPP) have been introduced recently, trading-off optimality for decreased planning time. In this paper, we revisit FocalSIPP and design several secondary heuristics for Focal Search with the intention to narrow the search in the direction of a preplanned optimal single-agent path not considering dynamic obstacles. The experimental results on various maps show that the designed heuristics generally outperform the hops-to-the-goal heuristic used in the original FocalSIPP and successfully compete with WSIPP as well. Copyright © 2021, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Motion planning

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How we can use text classification in the Back-Office environment of a bank as ‘business as usual’ solution

How we can use text classification in the Back-Office enviro...

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International Symposium on Applied Computational Intelligence and informatics ( SACI)

作者： Zsolt Krutilla Attila Kovari Doctoral School of Applied Informatics and Applied Mathematics Óbuda University Budapest Hungary Informatics Institution University of Dunaújváros Dunaújváros Hungary Institute of Engineering Alba Regia Technical Faculty Óbuda University Budapest Hungary Institute of Digital Technology Faculty of Informatics Eszterházy Károly Catholic University Eger Hungary Department of Natural Science Institute of Engineering University of Dunaújváros Dunaújváros Hungary GAMF Faculty of Engineering and Computer Science John von Neumann University Kecskemét Hungary

Natural Language Processing nowadays provides scientists with many research areas and opportunities, but as with most applied sciences, our goal in Natural Language Processing is to refine the underlying science and technology until it can be used reliably for business purposes. Transformer models, such as GPT or BERT, are currently showing outstanding results in the field of natural-language processing, but they require huge computational power and data to teach, but these conditions can only be met by larger research centers and large companies, and their inaccuracy makes them unsuitable for use as a ‘business as usual’ (BAU) solution. In this paper, we present a solution that is able to overcome these problems by focusing on accuracy and usability, and that can also bring a new perspective to the process of teaching deep learning models.

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A Novel Image Steganography Model Using LSB with Extended ASCII Codes 3rd

A Novel Image Steganography Model Using LSB with Extended AS...

引用

3rd International Conference on Smart Computing and informatics, SCI 2018

作者： Sai Ravi Chandra, N. Sneha, V. Victer Paul, P. Department of Biotechnology Guntur India Department of Computer Science and Engineering Vignan’s Foundation for Science Technology and Research GunturAndhra Pradesh India Department of Computer Science and Engineering Indian Institute of Information Technology Kottayam KottayamKerala India

ISBN: (纸本)9789811392818

Steganography is a method for invisible communication while concealing the actual data to be transmitted within non-secret data or text. It is the process of hiding the secret information within another form of data like text, image, audio, or video. Image steganography intends to embed a secret message into another image, called as a cover image through an encrypting algorithm, and the secret data can be retrieved by using a decrypting algorithm. The two major techniques used in image steganography process are spatial domain and transform domain. LSB is a commonly used technique as the payload capacity is higher compared to transform domain techniques, whereas the robustness is lower. There are various other models where the disadvantages of each type are being reduced. But the proposed model is a hybrid model which would increase payload capacity as well as robustness with a strong security. This helps to combine the advantages of each type of image steganography. We can do so by replacing the common words by using special symbols with extended ASCII values. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Steganography

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Deep Learning Landscapes and the Laby-Rinths of Logic Underlying Layers of Learning 2

Deep Learning Landscapes and the Laby-Rinths of Logic Underl...

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2nd IEEE International Conference on Innovations in High-Speed Communication and Signal Processing, IHCSP 2024

作者： Sharma, Divya Padmapriya, G. Wasatkar, N.N. Vijay, S. Arul Antran Aneja, Aseem Mythili, V. Chitkara University Chitkara Centre for Research and Development Himachal Pradesh 174103 India School of Sciences Chemistry and Biochemistry Karnataka Bangalore India Vishwakarma Institute of Technology Pune India Karpagam College of Engineering Department of Computer Science Engineering Coimbatore641032 India Chitkara University Centre of Research Impact and Outcome Punjab Rajpura140417 India Prince Shri Venkateshwara Padmavathy Engineering College Department of S&h Chennai127 India

ISBN: (纸本)9798350368949

The deep learning landscape and the logic labyrinths beneath it are examined in Deep Learning Landscapes and the Logic Labyrinths Under-lying Layers of Learning. The proposed strategy considers theory, model, and moral reflection from a broad perspective. This strategy simplifies deep learning, resulting in smarter, more moral models. The academic element of our technique details how deep learning models learn and make judgments, exhibiting neural network mathematical foundations. Model refinement and training methods require academic understanding. We have employed several deep learning approaches in academic and practical activities. CNNs, RNNs, LSTMs, transformers, and generative adversarial networks are examples. These solutions provide researchers and practitioners with hands-on expertise to improve model design and hyperparameters. We add ethics to our technique to address fairness, openness, and prejudice in deep learning systems. Our strategy promotes ethical AI development, resulting in fairer and more dependable models. The recommended strategy consistently outperforms the present one in accuracy, precision, recall, and F1. Ethical assessments reveal that the suggested technique is fairer, clearer, and less prejudiced than present methods. Due to its efficiency and morality, the proposed method is ideal for deep learning. © 2024 IEEE.

关键词： Convolutional neural networks

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Deep Learning Landscapes and the Laby-Rinths of Logic Underlying Layers of Learning

Deep Learning Landscapes and the Laby-Rinths of Logic Underl...

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Innovations in High Speed Communication and Signal Processing (IHCSP), International Conference on

作者： Divya Sharma G. PadmaPriya N.N. Wasatkar S. Arul Antran Vijay Aseem Aneja Mythili V Chitkara Centre for Research and Development Chitkara University Himachal Pradesh India School of Sciences Chemistry and Biochemistry JAIN (Deemed to be University) Bangalore Karnataka India COMP Vishwakarma Institute of Technology Pune India Department of Computer Science Engineering Karpagam College of Engineering Coimbatore India Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Department of S&H Prince Shri Venkateshwara Padmavathy Engineering College Chennai India

ISBN: (数字)9798350368949

ISBN: (纸本)9798350368956

关键词： Deep learning Training Ethics Technological innovation Accuracy Neural networks Transformers Mathematical models Logic Artificial intelligence

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