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arXiv 2024年

作者： Zhang, Keke Chen, Weiling Zhao, Tiesong Wang, Zhou Fujian Key Lab for Intelligent Processing and Wireless Transmission of Media Information College of Physics and Information Engineering Fuzhou University Fuzhou350108 China Fujian Science & Technology Innovation Laboratory for Optoelectronic Information of China Fuzhou350108 China Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada

Image Quality Assessment (IQA) with references plays an important role in optimizing and evaluating computer vision tasks. Traditional methods assume that all pixels of the reference and test images are fully aligned. Such Aligned-Reference IQA (AR-IQA) approaches fail to address many real-world problems with various geometric deformations between the two images. Although significant effort has been made to attack Geometrically-Disparate-Reference IQA (GDR-IQA) problem, it has been addressed in a task-dependent fashion, for example, by dedicated designs for image super-resolution and retargeting, or by assuming the geometric distortions to be small that can be countered by translation-robust filters or by explicit image registrations. Here we rethink this problem and propose a unified, non-training-based Deep Structural Similarity (DeepSSIM) approach to address the above problems in a single framework, which assesses structural similarity of deep features in a simple but efficient way and uses an attention calibration strategy to alleviate attention deviation. The proposed method, without application-specific design, achieves state-of-the-art performance on AR-IQA datasets and meanwhile shows strong robustness to various GDR-IQA test cases. Interestingly, our test also shows the effectiveness of DeepSSIM as an optimization tool for training image super-resolution, enhancement and restoration, implying an even wider generalizability. 1 Copyright © 2024, The Authors. All rights reserved.

关键词： Restoration

Multi-Agent Reinforcement Learning in Wireless Distributed Networks for 6G

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arXiv 2025年

作者： Zhang, Jiayi Liu, Ziheng Zhu, Yiyang Shi, Enyu Xu, Bokai Yuen, Chau Niyato, Dusit Debbah, Mérouane Jin, Shi Ai, Bo Shen, Xuemin School of Electronic and Information Engineering The Frontiers Science Center for Smart High-Speed Railway System Beijing jiaotong University Beijing100044 China School of Electrical and Electronics Engineering Nanyang Technological University 639798 Singapore College of Computing and Data Science Nanyang Technological University 639798 Singapore KU 6G Research Center Department of Computer and Information Engineering Khalifa University Abu Dhabi127788 United Arab Emirates CentraleSupelec University Paris-Saclay Gif-sur-Yvette91192 France National Mobile Communications Research Laboratory Southeast University Nanjing210096 China Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada

The introduction of intelligent interconnectivity between the physical and human worlds has attracted great attention for future sixth-generation (6G) networks, emphasizing massive capacity, ultra-low latency, and unparalleled reliability. Wireless distributed networks and multi-agent reinforcement learning (MARL), both of which have evolved from centralized paradigms, are two promising solutions for the great attention. Given their distinct capabilities, such as decentralization and collaborative mechanisms, integrating these two paradigms holds great promise for unleashing the full power of 6G, attracting significant research and development attention. This paper provides a comprehensive study on MARL-assisted wireless distributed networks for 6G. In particular, we introduce the basic mathematical background and evolution of wireless distributed networks and MARL, as well as demonstrate their interrelationships. Subsequently, we analyze different structures of wireless distributed networks from the perspectives of homogeneous and heterogeneous. Furthermore, we introduce the basic concepts of MARL and discuss two typical categories, including model-based and model-free. We then present critical challenges faced by MARL-assisted wireless distributed networks, providing important guidance and insights for actual implementation. We also explore an interplay between MARL-assisted wireless distributed networks and emerging techniques, such as information bottleneck and mirror learning, delivering in-depth analyses and application scenarios. Finally, we outline several compelling research directions for future MARL-assisted wireless distributed networks. Copyright © 2025, The Authors. All rights reserved.

关键词： Adversarial machine learning

Performance optimization of microbial electrolysis cell (MEC) for palm oil mill effluent (POME) wastewater treatment and sustainable Bio-H2 production using response surface methodology (RSM)

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INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 2022年第34期47卷 15464-15479页

作者： Chandrasekhar, Abudukeremu Kadier ab Junying Wang ab K. Wang, Junying Chandrasekhar, K. Abdeshahian, Peyman Islam, M. Amirul Ghanbari, Farshid Bajpai, Mukul Katoch, Surjit Singh Bhagawati, Prashant Basavaraj Li, Hui Kalil, Mohd Sahaid Hamid, Aidil Abdul Abu Hasan, Hassimi Ma, Peng-Cheng [a]Laboratory of Environmental Science and Technology The Xinjiang Technical Institute of Physics and Chemistry Key Laboratory of Functional Materials and Devices for Special Environments Chinese Academy of Sciences Urumqi 830011 China [b]Center of Material and Opto-electronic Research University of Chinese Academy of Sciences Beijing 100049 China [c]School of Civil and Environmental Engineering Yonsei University Seoul 03722 Republic of Korea [d]Department of Biotechnology Engineering School of Lorena University of São Paulo São Paulo 12602-810 Brazil [e]Laboratory for Quantum Semiconductors and Photon-based BioNanotechnology Department of Electrical and Computer Engineering Faculty of Engineering Université de Sherbrooke Sherbrooke Québec J1K 2R1 Canada [f]Research Center for Environmental Contaminants (RCEC) Abadan University of Medical Sciences Abadan Iran [g]Environmental Engineering Lab Civil Engineering Department National Institute of Technology Hamirpur Hamirpur Himachal Pradesh 177005 India [h]Faculty of Engineering Department of Civil Engineering Annasaheb Dange College of Engineering and Technology Ashta Maharashtra 416301 India [i]Department of Chemical and Process Engineering Faculty of Engineering and Built Environment National University of Malaysia (UKM) UKM Bangi 43600 Selangor Malaysia [j]School of Biosciences and Biotechnology Faculty of Science and Technology National University of Malaysia (UKM) UKM Bangi 43600 Selangor Malaysia [k]Research Centre for Sustainable Process Technology Faculty of Engineering and Built Environment National University of Malaysia (UKM) UKM Bangi 43600 Selangor Malaysia

Microbial electrolysis cells (MECs) are a new bio-electrochemical method for converting organic matter to hydrogen gas (H-2). Palm oil mill effluent (POME) is hazardous wastewater that is mostly formed during the crude oil extraction process in the palm oil industry. In the present study, POME was used in the MEC system for hydrogen generation as a feasible treatment technology. To enhance biohydrogen generation from POME in the MEC, an empirical model was generated using response surface methodology (RSM). A central composite design (CCD) was utilized to perform twenty experimental runs of MEC given three important variables, namely incubation temperature, initial pH, and influent dilution rate. Experimental results from CCD showed that an average value of 1.16 m(3) H-2/m(3) d for maximum hydrogen production rate (HPR) was produced. A second-order polynomial model was adjusted to the experimental results from CCD. The regression model showed that the quadratic term of all variables tested had a highly significant effect (P < 0.01) on maximum HPR as a defined response. The analysis of the empirical model revealed that the optimal conditions for maximum HPR were incubation temperature, initial pH, and influent dilution rate of 30.23 ?, 6.63, and 50.71%, respectively. Generated regression model predicted a maximum HPR of 1.1659 m(3) H-2/m(3) d could be generated under optimum conditions. Confirmation experimentation was conducted in the optimal conditions determined. Experimental results of the validation test showed that a maximum HPR of 1.1747 m(3) H-2/m(3) d was produced. (c) 2021 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

关键词： Microbial electrolysis cell (MEC) Hydrogen production Palm oil mill effluent (POME) Wastewater Optimization Response surface methodology (RSM)

Research on Coverless Image Steganography

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International Journal of Network Security 2023年第1期25卷 25-31页

作者： Anggriani, Kurnia Wu, Nan-I Hwang, Min-Shiang Department of Computer Science & Information Engineering Asia University 500Lioufeng Rd.Wufeng Taichung41354 Taiwan Faculty of Engineering University of Bengkulu Indonesia Department of Digital Multimedia Lee-Ming Institute of Technology No.2-2Lijhuan Rd.Taishan TownshipCounty 243 Taipei Taiwan Department of Medical Research China Medical University Hospital China Medical University Taiwan

In recent years, Coverless Image Steganography (CIS) has become an essential research topic for many scholars. This research topic was initiated in 2015 under steganography without embedding. Accordingly, CIS was presented to withstand the inadequacies of the general steganography method against the risks of steganalysis tools. This is because information concealed in CIS has no modification left on the stego image. Conversely, CIS performs a mapping operation to select a stego image containing secret information. This paper attempts to examine the development of CIS over the past five years, summarizing and analyzing the benefits and challenges of the current methods used by each survey paper. Moreover, we present the experimental results in tables and graphs to provide a precise performance comparison. This is done to outline future research requirements and opportunities in the CIS research topic. For example, in the future, developing a CIS method that is resistant to steganalysis tools, has a large hiding capacity, and can be used in real-time applications would be ideal. © 2022,International Journal of Network Security. All Rights Reserved.

关键词： Mapping

Hybrid Precoding for Mixture Use of Phase Shifters and Switches in mmWave Massive MIMO

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arXiv 2022年

作者： Qi, Chenhao Liu, Qiang Yu, Xianghao Li, Geoffrey Ye The School of Information Science and Engineering Southeast University Nanjing210096 China The Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology 999077 Hong Kong The Department of Electrical and Electronic Engineering Imperial College London LondonSW7 2AZ United Kingdom

A variable-phase-shifter (VPS) architecture with hybrid precoding for mixture use of phase shifters and switches, is proposed for millimeter wave massive multiple-input multiple-output communications. For the VPS architecture, a hybrid precoding design (HPD) scheme, called VPS-HPD, is proposed to optimize the phases according to the channel state information by alternately optimizing the analog precoder and digital precoder. To reduce the computational complexity of the VPS-HPD scheme, a low-complexity HPD scheme for the VPS architecture (VPS-LC-HPD) including alternating optimization in three stages is then proposed, where each stage has a closed-form solution and can be efficiently implemented. To reduce the hardware complexity introduced by the large number of switches, we consider a group-connected VPS architecture and propose a HPD scheme, where the HPD problem is divided into multiple independent subproblems with each subproblem flexibly solved by the VPS-HPD or VPS-LC-HPD scheme. Simulation results verify the effectiveness of the propose schemes and show that the proposed schemes can achieve satisfactory spectral efficiency performance with reduced computational complexity or hardware complexity. Copyright © 2022, The Authors. All rights reserved.

关键词： Millimeter waves

Explainable artificial intelligence for human decision-support system in medical domain

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arXiv 2021年

作者： Knapič, Samanta Malhi, Avleen Saluja, Rohit Främling, Kary Department of Computer Science Aalto University Konemiehentie 2 Espoo02150 Finland Department of Computing Science UmeåUniversity Umeå90187 Sweden Department of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden

In the present paper we present the potential of Explainable Artificial Intelligence methods for decision-support in medical image analysis scenarios. With three types of explainable methods applied to the same medical image data set our aim was to improve the comprehensibility of the decisions provided by the Convolutional Neural Network (CNN). The visual explanations were provided on in-vivo gastral images obtained from a Video capsule endoscopy (VCE), with the goal of increasing the health professionals' trust in the black box predictions. We implemented two post-hoc interpretable machine learning methods LIME and SHAP and the alternative explanation approach CIU, centered on the Contextual Value and Utility (CIU). The produced explanations were evaluated using human evaluation. We conducted three user studies based on the explanations provided by LIME, SHAP and CIU. Users from different non-medical backgrounds carried out a series of tests in the web-based survey setting and stated their experience and understanding of the given explanations. Three user groups (n=20, 20, 20) with three distinct forms of explanations were quantitatively analyzed. We have found that, as hypothesized, the CIU explainable method performed better than both LIME and SHAP methods in terms of increasing support for human decision-making as well as being more transparent and thus understandable to users. Additionally, CIU outperformed LIME and SHAP by generating explanations more rapidly. Our findings suggest that there are notable differences in human decision-making between various explanation support settings. In line with that, we present three potential explainable methods that can with future improvements in implementation be generalized on different medical data sets and can provide great decision-support for medical experts. © 2021, CC BY-NC-SA.

关键词： Decision support systems

OntoM: An Ontological Approach for Automatic Classification

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OntoM: An Ontological Approach for Automatic Classification

2020 IEEE International Conference on Informatics, IoT, and Enabling Technologies, ICIoT 2020

作者： Musa, Tahani H. Abu Bouras, Abdelaziz Belhi, Abdelhak Gasmi, Houssem College of Engineering Qatar University Department of Computer Science and Engineering Doha Qatar DISP Laboratory Université Lumiére Lyon 2 Lyon France

ISBN: (纸本)9781728148212

The concept of Ontologies has been used in a wide range of application domains, due to the fact that ontologies provide a useful mean for establishing a formal, shared and collective understanding of the concepts and their underlying relations at a certain domain of interest, which allows for interoperability and information exchange in a formal an understandable way for both humans and machines. In Cultural Heritage (CH) domain, ontologies serve as a fundamental building block for the traceability of the cultural heritage objects, especially with the increasing demand of providing digital formats for cultural objects and make them available for public. In this paper we implement OntoM;an Ontology model that incorporates the relevant concepts of the Cultural Heritage (CH) domain in Qatar. Then, we will use such an ontology to perform inferences about cultural object classifications via two approaches: string matching, that allows for direct matching between the object and the ontology concepts, and semantic matching, in which we use WordNet lexical database to find all possible synonyms for properties of a given anonymous object. © 2020 IEEE.

关键词： Ontology

A Thin Film Barium Titanate-on-Insulator Optoelectronics Platform with Various Photonic Devices

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A Thin Film Barium Titanate-on-Insulator Optoelectronics Pla...

CLEO: science and Innovations, S and I 2022

作者： Cao, Yu Ng, Jun Da Lin, Hong-Lin Shao, Jianbo Qi, Luo Siew, Shawn Yohanes Dogheche, Elhadj Danner, Aaron J. Department of Electrical and Computer Engineering National University of Singapore 4 Engineering Drive 3 Singapore117583 Singapore Advanced Micro Foundry 11 Science Park Road Singapore117685 Singapore Microsoft Research 21 Station Road CambridgeCB1 2FB United Kingdom Institute of Electronics Microelectronics and Nanotechnology IEMN DOAE Université Polytechnique Hauts-de-France Valenciennes59309 France

We present a thin-film barium titanate-on-insulator platform and its optical and electrooptic properties, some of which are superior to lithium niobate-on-insulator, and discuss our progress in device fabrication, per... 详细信息

ISBN: (纸本)9781557528209

关键词： Barium titanate

Synthesis of Energy-Conserving Quantum Circuits with XY interaction

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arXiv 2023年

作者： Bai, Ge Marvian, Iman Centre for Quantum Technologies National University of Singapore 3 Science Drive 2 Singapore117543 Singapore QICI Quantum Information and Computation Initiative Department of Computer Science The University of Hong Kong Pokfulam Road Hong Kong HKU-Oxford Joint Laboratory for Quantum Information and Computation Hong Kong Duke Quantum Center Departments of Electrical and Computer Engineering and Physics Duke University DurhamNC27708 United States

We study quantum circuits constructed from √iSWAP gates and, more generally, from the entangling gates that can be realized with the XX+YY interaction alone. Such gates preserve the Hamming weight of states in the computational basis, which means they respect the global U(1) symmetry corresponding to rotations around the z axis. Equivalently, assuming that the intrinsic Hamiltonian of each qubit in the system is the Pauli Z operator, they conserve the total energy of the system. We develop efficient methods for synthesizing circuits realizing any desired energy-conserving unitary using XX+YY interaction with or without single-qubit rotations around the z-axis. Interestingly, implementing generic energy-conserving unitaries, such as CCZ and Fredkin gates, with 2-local energy-conserving gates requires the use of ancilla qubits. When single-qubit rotations around the z-axis are permitted, our scheme requires only a single ancilla qubit, whereas with the XX+YY interaction alone, it requires 2 ancilla qubits. In addition to exact realizations, we also consider approximate realizations and show how a general energy-conserving unitary can be synthesized using only a sequence of √iSWAP gates and 2 ancillary qubits, with arbitrarily small error, which can be bounded via the Solovay-Kitaev theorem. Our methods are also applicable for synthesizing energy-conserving unitaries when, rather than the XX+YY interaction, one has access to any other energy-conserving 2-body interaction that is not diagonal in the computational basis, such as the Heisenberg exchange interaction. We briefly discuss the applications of these circuits in the context of quantum computing, quantum thermodynamics, and quantum clocks. Copyright © 2023, The Authors. All rights reserved.

关键词： Qubits