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SSRN 2024年

作者： Ueda, Tenma Otabe, Edmund Soji Arita, Ken Usami, Yuki Tanaka, Hirofumi Matsuno, Tetsuya Department of Physics and Computer Science Kyushu Institute of Technology 680–4 Kawazu Iizuka Fukuoka820–8502 Japan Department of Human Intelligence Systems Graduate School of Life Science and Systems Engineering Kyushu Institute of Technology 2–4 Hibikino Wakamatsu Kitakyushu808–019 Japan Research Center for Neuromorphic AI Hardware Kyushu Institute of Technology 2–4 Hibikino Wakamatsu Kitakyushu808–019 Japan Department of Creative Engineering National Institute of Technology Ariake College 150 Higashihagio-Machi Omuta Fukuoka836-8585 Japan

Reservoir computing, which takes advantage of physical phenomena with nonlinearities, is attracting a lot of ***, it is expected to focus on superconductivity, a physical phenomenon with nonlinearities between the output electric field and the input current *** to other physical phenomena used in reservoirs, it is considered that with superconductivity, the nonlinearity can easily be adjusted spatially by pin placement to produce dynamics suitable for *** nonlinearity between the electric field generated by the motion of the quantized magnetic flux lines and the input current density was used to perform a reservoir computing *** waveform generation tasks, a NARMA2 task and a nonlinear-memory task were performed, and all tasks were generally *** was found that the electromagnetic phenomenon in superconductors can be used as a physical reservoir. © 2024, The Authors. All rights reserved.

关键词： Electric lines

Inverted-circuit zero-noise extrapolation for quantum gate error mitigation

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arXiv 2024年

作者： Koenig, Kathrin F. Reinecke, Finn Hahn, Walter Wellens, Thomas Fraunhofer Institute for Applied Solid State Physics Tullastr. 72 Freiburg79108 Germany Department of Sustainable Systems Engineering University of Freiburg Emmy-Noether-Str. 2 Freiburg79110 Germany Department of Computer Science University of Freiburg Georges-Köhler-Allee 51 Freiburg79110 Germany

A common approach to deal with gate errors in modern quantum-computing hardware is zero-noise extrapolation. By artificially amplifying errors and extrapolating the expectation values obtained with different error strengths towards the zero-error (zero-noise) limit, the technique aims at rectifying errors in noisy quantum computing systems. For accurate extrapolation, it is essential to know the exact factors of the noise amplification. In this article, we propose a simple method for estimating the strength of errors occurring in a quantum circuit and demonstrate improved extrapolation results. The method determines the error strength for a circuit by appending to it the inverted circuit and measuring the probability of the initial state. The estimation of error strengths is easy to implement for arbitrary circuits and does not require previous characterization of noise properties. We compare this method with the conventional zero-noise extrapolation method and show that our method leads to a more accurate calculation of expectation values on current quantum hardware, showcasing its suitability for near-term quantum computing applications. © 2024, CC BY.

关键词： Quantum computers

Collision-free motion control with learning features for automated vehicles in roundabouts

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Transportation Research Procedia 2023年 72卷 3545-3552页

作者： Balázs Németh Zsófia Farkas Zoltán Antal Dániel Fényes Péter Gáspár Institute for Computer Science and Control (SZTAKI) Eötvös Loránd Research Network (ELKH) Kende utca 13-15. 1111 Budapest Hungary Budapest University of Technology and Economics Department of Control for Transportation and Vehicle Systems Stoczek utca 2. 1111 Budapest Hungary

Control design for safe and time-efficient motion of automated vehicles in roundabout scenarios poses various challenges, especially adaptation to the actual traffic scenario and coordination of the vehicles. This paper proposes the design of a hierarchical motion control with learning feature for roundabout scenarios. The control is designed on two levels, such as on cloud level and on vehicle level. The control on the cloud level is designed by using reinforcement learning ( RL ), with which the energy efficient motion of the vehicle is achieved. The vehicle level contains a robust controller and a supervisor, with which the collision avoidance of the vehicles is guaranteed. The proposed control on a Hardware-in-the-Loop environment with small-scaled indoor vehicles in augmented reality is implemented. The effectiveness of the control and the safe motion of the automated vehicles under multi -vehicle scenario are demonstrated. The provided scenario illustrates that safe, i.e., collision-free motion of all automated vehicles can be guaranteed.

关键词： automated vehicles learning features roundabouts collision-free motion control design

A cell growth model accounting for both ribosomal sub-units synthesis: conditions for the exponential growth

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IFAC-PapersOnLine 2023年第2期56卷 7240-7245页

作者： Pasquale Palumbo Stefano Busti Marco Vanoni Department of Biotechnology and Biosciences University of Milano-Bicocca Piazza della Scienza 2 20126 Milan Italy SYSBIO- ISBE 20126 Milan Italy Institute for Systems Analysis and Computer Science “A. Ruberti” National Research Council (IASI-CNR) Via dei Taurini 19 00185 Rome Italy

Ribosomes play a pivotal role in cell growth, since they are deputed to build amino acids for proteins assembly. Ribosomes consist of a small and a large sub-unit, whose binding occurs on mRNA strands. Both small and large sub-units origin from a common precursor of rRNA. In this note we propose a novel model of cell growth explicitly dealing with small and large ribosomal sub-units, as well as with their common precursor. Proteins are also included, since it is known they exert a control feedback on ribosome biogenesis: the modeling assumption is that the precursor synthesis is switched off when the ribosome-over-protein ratio exceeds a given threshold. The qualitative analysis of the proposed model is carried out with the aim of showing that there exist conditions on the model parameters according to which the exponential growth is ensured, that means all the state variables have an exponential time law, all sharing the same (positive) exponential growth rate. The model parameters have been assessed in order to provide meaningful time evolution of all the molecular players involved, and to result consistent with an existing, less complex model of cellular growth accounting for only ribosomes and proteins, recently exploited as a growth module inside a scaffold whole-cell model connecting metabolism, growth and cycle for the budding yeast Saccharomyces cerevisiae, the experimental model usually exploited for eukaryotic cells.

关键词： systems Biology Mathematical modeling Qualitative behavior analysis

A Single Channel-Based Neonatal Sleep-Wake Classification using Hjorth Parameters and Improved Gradient Boosting

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arXiv 2024年

作者： Arslan, Muhammad Mubeen, Muhammad Abbasi, Saadullah Farooq Khan, Muhammad Shahbaz Boulila, Wadii Ahmad, Jawad Department of Computer Science Loyola University ChicagoIL60660 United States Department of Computer Science University of People PasadenaCA91101 United States Department of Electronic Electrical and Systems Engineering University of Birmingham BirminghamB15 2TT United Kingdom School of Computing Engineering and the Built Environment Edinburgh Napier University EdinburghEH105DT United Kingdom RIOTU Lab Prince Sultan University Riyadh12435 Saudi Arabia

Sleep plays a crucial role in neonatal development. Monitoring the sleep patterns in neonates in a Neonatal Intensive Care Unit (NICU) is imperative for understanding the maturation process. While polysomnography (PSG) is considered the best practice for sleep classification, its expense and reliance on human annotation pose challenges. Existing research often relies on multichannel EEG signals;however, concerns arise regarding the vulnerability of neonates and the potential impact on their sleep quality. This paper introduces a novel approach to neonatal sleep stage classification using a single-channel gradient boosting algorithm with Hjorth features. The gradient boosting parameters are fine-tuned using random search cross-validation (randomsearchCV), achieving an accuracy of 82.35% for neonatal sleep-wake classification. Validation is conducted through 5-fold cross-validation. The proposed algorithm not only enhances existing neonatal sleep algorithms but also opens avenues for broader applications. © 2024, CC BY.

关键词： Neonatal monitoring

Toward Energy Efficient Multiuser IRS-Assisted URLLC systems: A Novel Rank Relaxation Method

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arXiv 2023年

作者： Jalali, Jalal Lemic, Filip Tabassum, Hina Berkvens, Rafael Famaey, Jeroen IDLab University of Antwerp - imec Sint-Pietersvliet 7 Antwerp2000 Belgium AI-Driven Systems Lab i2Cat Foundation Barcelona Spain Department of Electrical Engineering and Computer Science York University TorontoON Canada

This paper proposes an energy efficient resource allocation design algorithm for an intelligent reflecting surface (IRS)-assisted downlink ultra-reliable low-latency communication (URLLC) network. This setup features a multi-antenna base station (BS) transmitting data traffic to a group of URLLC users with short packet lengths. We maximize the total network’s energy efficiency (EE) through the optimization of active beamformers at the BS and passive beamformers (a.k.a phase shifts) at the IRS. The main non-convex problem is divided into two sub-problems. An alternating optimization (AO) approach is then used to solve the problem. Through the use of the successive convex approximation (SCA) with a novel iterative rank relaxation method, we construct a concave-convex objective function for each sub-problem. The first sub-problem is a fractional program that is solved using the Dinkelbach method and a penalty-based approach. The second sub-problem is then solved based on semi-definite programming (SDP) and the penalty-based approach. The iterative solution gradually approaches the rank-one for both the active beamforming and unit modulus IRS phase-shift sub-problems. Our results demonstrate the efficacy of the proposed solution compared to existing benchmarks. © 2023, CC BY.

关键词： Beamforming

A Comprehensive Survey of Spectrum Sharing Schemes from a Standardization and Implementation Perspective

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arXiv 2022年

作者： Parvini, Mohammad Zarif, Amir Hossein Nouruzi, Ali Mokari, Nader Javan, Mohammad Reza Abbasi, Bijan Ghasemi, Amir Yanikomeroglu, Halim The Department of Electrical and Computer Engineering Tarbiat Modares University Tehran Iran The Department of Electrical and Computer Engineering Shahrood University of Technology Iran The Commutations Research Centre Innovation Science and Economic Development Canada OttawaONK2H 8S2 Canada The Department of Systems and Computer Engineering Carleton University Ottawa Canada

As the services and requirements of next-generation wireless networks become increasingly diversified, it is estimated that the current frequency bands of mobile network operators (MNOs) will be unable to cope with the immensity of anticipated demands. Due to spectrum scarcity, there has been a growing trend among stakeholders toward identifying practical solutions to make the most productive use of the exclusively allocated bands on a shared basis through spectrum sharing mechanisms. However, due to the technical complexities of these mechanisms, their design presents challenges, as it requires coordination among multiple entities. To address this challenge, in this paper, we begin with a detailed review of the recent literature on spectrum sharing methods, classifying them on the basis of their operational frequency regime-that is, whether they are implemented to operate in licensed bands (e.g., licensed shared access (LSA), spectrum access system (SAS), and dynamic spectrum sharing (DSS)) or unlicensed bands (e.g., LTE-unlicensed (LTE-U), licensed assisted access (LAA), MulteFire, and new radio-unlicensed (NR-U)). Then, in order to narrow the gap between the standardization and vendor-specific implementations, we provide a detailed review of the potential implementation scenarios and necessary amendments to legacy cellular networks from the perspective of telecom vendors and regulatory bodies. Next, we analyze applications of artificial intelligence (AI) and machine learning (ML) techniques for facilitating spectrum sharing mechanisms and leveraging the full potential of autonomous sharing scenarios. Finally, we conclude the paper by presenting open research challenges, which aim to provide insights into prospective research endeavors. © 2022, CC BY.

关键词： Standardization

Non-convex potential games for finding global solutions to sensor network localization

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arXiv 2023年

作者： Xu, Gehui Chen, Guanpu Hong, Yiguang Fidan, Baris Parisini, Thomas Johansson, Karl H. Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Beijing China Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm100 44 Sweden Department of Control Science and Engineering Tongji University Shanghai201804 China Shanghai Research Institute for Intelligent Autonomous Systems Shanghai201210 China Department of Mechanical and Mechatronics Engineering University of Waterloo WaterlooONN2L 3G1 Canada Department of Electrical and Electronic Engineering Imperial College London LondonSW7 2AZ United Kingdom Department of Engineering and Architecture University of Trieste Trieste34127 Italy

Sensor network localization (SNL) problems require determining the physical coordinates of all sensors in a network. This process relies on the global coordinates of anchors and the available measurements between non-anchor and anchor nodes. Attributed to the intrinsic non-convexity, obtaining a globally optimal solution to SNL is challenging, as well as implementing corresponding algorithms. In this paper, we formulate a non-convex multi-player potential game for a generic SNL problem to investigate the identification condition of the global Nash equilibrium (NE) therein, where the global NE represents the global solution of SNL. We employ canonical duality theory to transform the non-convex game into a complementary dual problem. Then we develop a conjugation-based algorithm to compute the stationary points of the complementary dual problem. On this basis, we show an identification condition of the global NE: the stationary point of the proposed algorithm satisfies a duality relation. Finally, simulation results are provided to validate the effectiveness of the theoretical results. Copyright © 2023, The Authors. All rights reserved.

关键词： Sensor networks

Knowledge Graph Completion with Low-Dimensional Gated Hierarchical Hyperbolic Embedding

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SSRN

SSRN 2024年

作者： Fang, Yan Liu, Xiaodong Lu, Wei Pedrycz, Witold Lang, Qi Yang, Jianhua School of Control Science and Engineering Faculty of Electronic Information and Electrical Engineering Dalian University of Technology Dalian116024 China Department of Electrical and Computer Engineering University of Alberta EdmontonT6R 2V4 AB Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland Department of Electrical and Computer Engineering Faculty of Engineering King Abdulaziz University Jeddah21589 Saudi Arabia School of Computer Science and Information Technology Northeast Normal University Changchun130117 China

Knowledge Graph Embedding aims to advance the learning performance of knowledge graphs by deliberating the complexity of hierarchical data structures in a finite-dimensional space. Most traditional Euclidean models struggle to accurately describe and navigate the intricate hierarchical relationships between nodes. The hyperbolic embedding methods, particularly in conjunction with graph neural networks, offer promise in effectively modeling complex hierarchies in a limited-dimensional space. These methods can accommodate more information about nodes under the same conditions but are also more susceptible to interference from complex neighborhood features. This paper introduces HyperGatE, which novelty combines a hyperbolic graph hierarchical neighbor structure based on a gated filter and a hyperbolic isometric rotation model for knowledge graph completion. By analyzing the hierarchical structure of the knowledge base and using a gated mechanism to form multi-layer embedding networks of entity-relational paths, the gated filter selects diverse uneven multi-hop relations within the entity neighborhood and measures them through graph attention networks. Furthermore, the simplified hyperbolic isometric model allows for uncovering hierarchical structures in the data. HyperGatE experimentally surpasses the state-of-the-art Euclidean and hyperbolic space models in high and low dimensions across four well-known data, namely WN18RR, FB15k-237, NELL-995, and Kinship. © 2024, The Authors. All rights reserved.

关键词： Knowledge graph

A hierarchical fusion strategy of deep learning networks for detection and segmentation of hepatocellular carcinoma from computed tomography images

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Cancer Imaging 2024年第1期24卷 1页

作者： Lee, I-Cheng Tsai, Yung-Ping Lin, Yen-Cheng Chen, Ting-Chun Yen, Chia-Heng Chiu, Nai-Chi Hwang, Hsuen-En Liu, Chien-An Huang, Jia-Guan Lee, Rheun-Chuan Chao, Yee Ho, Shinn-Ying Huang, Yi-Hsiang Division of Gastroenterology and Hepatology Department of Medicine Taipei Veterans General Hospital Taipei Taiwan School of Medicine National Yang Ming Chiao Tung University Taipei Taiwan Institute of Bioinformatics and Systems Biology National Yang Ming Chiao Tung University Hsinchu Taiwan Institute of Computer Science and Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Radiology Taipei Veterans General Hospital Taipei Taiwan National Taiwan University School of Medicine Taipei Taiwan Cancer Center Taipei Veterans General Hospital Taipei Taiwan Department of Biological Science and Technology National Yang Ming Chiao Tung University Hsinchu Taiwan Center for Intelligent Drug Systems and Smart Bio-devices (IDS 2 B) National Yang Ming Chiao Tung University Hsinchu Taiwan College of Health Sciences Kaohsiung Medical University Kaohsiung Taiwan Institute of Clinical Medicine National Yang Ming Chiao Tung University Taipei Taiwan Healthcare and Service Center Taipei Veterans General Hospital Taipei Taiwan

Background: Automatic segmentation of hepatocellular carcinoma (HCC) on computed tomography (CT) scans is in urgent need to assist diagnosis and radiomics analysis. The aim of this study is to develop a deep learning based network to detect HCC from dynamic CT images. Methods: Dynamic CT images of 595 patients with HCC were used. Tumors in dynamic CT images were labeled by radiologists. Patients were randomly divided into training, validation and test sets in a ratio of 5:2:3, respectively. We developed a hierarchical fusion strategy of deep learning networks (HFS-Net). Global dice, sensitivity, precision and F1-score were used to measure performance of the HFS-Net model. Results: The 2D DenseU-Net using dynamic CT images was more effective for segmenting small tumors, whereas the 2D U-Net using portal venous phase images was more effective for segmenting large tumors. The HFS-Net model performed better, compared with the single-strategy deep learning models in segmenting small and large tumors. In the test set, the HFS-Net model achieved good performance in identifying HCC on dynamic CT images with global dice of 82.8%. The overall sensitivity, precision and F1-score were 84.3%, 75.5% and 79.6% per slice, respectively, and 92.2%, 93.2% and 92.7% per patient, respectively. The sensitivity in tumors < 2 cm, 2–3, 3–5 cm and > 5 cm were 72.7%, 92.9%, 94.2% and 100% per patient, respectively. Conclusions: The HFS-Net model achieved good performance in the detection and segmentation of HCC from dynamic CT images, which may support radiologic diagnosis and facilitate automatic radiomics analysis. © The Author(s) 2024.

关键词： Computed tomography Deep learning Detection Hepatocellular carcinoma Segmentation