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IEEE Transactions on Nanobioscience 2025年 PP卷 PP页

作者： Liu, Zhenlu Cao, Ben Shao, Qi Zheng, Yanfen Wang, Bin Zhou, Shihua Zheng, Pan Dalian University Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian116622 China Dalian University of Technology School of Computer Science and Technology Dalian116024 China University of Canterbury Upper Riccarton Department of Accounting and Information Systems Christchurch8140 New Zealand

Deoxyribonucleic acid (DNA) has become an ideal medium for long-term storage and retrieval due to its extremely high storage density and long-term stability. But access efficiency is an existing bottleneck in DNA storage, especially the lack of high-quality random access address sequences. Therefore, in this paper, we report a series of approaches based on k-weakly mutually uncorrelated (k-WMU) codes to design the address sequence to improve the access efficiency of DNA storage. To address the problem of DNA sequences that are poorly scalable at the base level, we propose a 0-m-ruling coding scheme combined with k-WMU codes that can make address sequences avoid generating secondary structure with stem lengths ranging from 3 to 9. Based on the decoupled structure, We further extend the k-WMU codes with error correction function while satisfying combinatorial biological constraints. In order to investigate the performance of the designed address sequences for real-world applications, we perform simulation experiments based on thermodynamic properties and error correction capability as well as compared the minimum free energy (MFE), melting temperature (TM), and average decoding success rate (ADSR) with previous work. The results show that designed address sequences have a high MFE value and ADSR and a substantial reduction in TM-variance while satisfying the combinatorial biological constraints. As the quality of address sequences improves, this will help to achieve accurate random access as well as enhance the robustness of the DNA storage system. © 2002-2011 IEEE.

关键词： DNA sequences

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Deep learning-based denoising in projection-domain and reconstruction-domain for low-dose myocardial perfusion SPECT

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Journal of Nuclear Cardiology 2023年第3期30卷 970-985页

作者： Sun, Jingzhang Jiang, Han Du, Yu Li, Chien-Ying Wu, Tung-Hsin Liu, Yi-Hwa Yang, Bang-Hung Mok, Greta S. P. Biomedical Imaging Laboratory (BIG) Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau Macao Department of Biomedical Imaging and Radiological Sciences National Yang Ming Chiao Tung University Taipei Taiwan Department of Nuclear Medicine Taipei Veterans General Hospital Taipei Taiwan Department of Internal Medicine Yale University School of Medicine New Haven CT United States

Background: Low-dose (LD) myocardial perfusion (MP) SPECT suffers from high noise level, leading to compromised diagnostic accuracy. Here we investigated the denoising performance for MP-SPECT using a conditional generative adversarial network (cGAN) in projection-domain (cGAN-prj) and reconstruction-domain (cGAN-recon). Methods: Sixty-four noisy SPECT projections were simulated for a population of 100 XCAT phantoms with different anatomical variations and ^99mTc-sestamibi distributions. Series of LD projections were obtained by scaling the full dose (FD) count rate to be 1/20 to 1/2 of the original. Twenty patients with ^99mTc-sestamibi stress SPECT/CT scans were retrospectively analyzed. For each patient, LD SPECT images (7/10 to 1/10 of FD) were generated from the FD list mode data. All projections were reconstructed by the quantitative OS-EM method. A 3D cGAN was implemented to predict FD images from their corresponding LD images in the projection- and reconstruction-domain. The denoised projections were reconstructed for analysis in various quantitative indices along with cGAN-recon, Gaussian, and Butterworth-filtered images. Results: cGAN denoising improves image quality as compared to LD and conventional post-reconstruction filtering. cGAN-prj can further reduce the dose level as compared to cGAN-recon without compromising the image quality. Conclusions: Denoising based on cGAN-prj is superior to cGAN-recon for MP-SPECT. © 2022, The Author(s) under exclusive licence to American Society of Nuclear Cardiology.

关键词： deep learning low dose myocardial perfusion SPECT projection reconstruction

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BTDFS: B+ Tree-Based Distributed File Storing Mechanism for Improving Small File Storage

BTDFS: B+ Tree-Based Distributed File Storing Mechanism for ...

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IEEE International Conference on High Performance Computing and Communications (HPCC)

作者： Jingyu Zhang Jiachen Tian Lailong Luo School of Computer & Communication Engineering Changsha University of Science & Technology Changsha China Science and Technology on Information Systems Engineering Laboratory School of Systems Engineering National University of Defense Technology Changsha China

Hadoop is currently the most popular big data processing architecture, which provides a processing framework for managing and analyzing massive data. Hadoop Distributed File System (HDFS) is the core component for storing data in the Hadoop systems. It performs well when storing and managing large-sized files. However, it shows extremely bad performance when dealing with a large number of small files, which is reflected in the consumption of a large amount of memory space of the NameNode node and the low efficiency of accessing small files. Archive file is proposed to solve this problem. It combines small files into larger merged files for storage, and uses index files to record the relevant information of small files in the merged files. However, archive files (e.g., Hadoop Archive, MapFile) all require additional processing and multiple I/O operations to obtain index information before actually accessing the file content, which reduces the efficiency of file access. This paper proposes a novel distributed file storing mechanism called B+ Tree-Based Distributed File Storing mechanism (BTDFS), which combines a large number of small files into a merged file, records the index information of the small files in the merged file, and organizes the index information into a B+ tree for storage. Using BTDFS, while reducing the metadata consumption of the NameNode node, improves the access performance of a single small file with additional abilities, which provides convenience for analyzing a large number of small files. Finally, this paper designs corresponding experiments for the proposed BTDFS, and tests and analyzes the memory usage in N ameN ode and the access performance of small files. The experimental results show that the proposed BTDFS can effectively reduce the memory usage of the NameNode, and the efficiency of accessing small files is improved compared with state-of-the-art methods.

关键词： File systems Memory management Distributed databases Big Data Metadata Indexing

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Out-of-Distribution Fault Diagnosis of Industrial Cyber-Physical systems Based on Orthogonal Anchor Clustering With Adaptive Balance

IEEE Transactions on Industrial Cyber-Physical Systems

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IEEE Transactions on Industrial Cyber-Physical systems 2025年 3卷 48-60页

作者： Liu, Ruonan Hu, Puyuan Zhao, Siheng Sun, Zhijian Han, Te Pang, Zhibo Zhang, Weidong Shanghai Jiao Tong University Department of Automation Shanghai200240 China National Key Laboratory of Marine Engine Science and Technology Shanghai201108 China Crossocean of Suzhou Technology Suzhou215121 China Beijing Institute of Technology Center for Energy and Environmental Policy Research School of Management Beijing100081 China ABB Corporate Research Sweden Department of Automation Technology Vasteras722 26 Sweden KTH Royal Institute of Technology Department of Intelligent Systems Stockholm114 28 Sweden Henan University Henan Key Laboratory of Big Data Analysis and Processing School of Computer and Information Engineering Kaifeng475001 China Shanghai Jiaotong University Department of Automation Shanghai200240 China

Given the critical role of rotating machinery in industrial cyber-physical systems (ICPS), ensuring their reliable operation is essential for the stability and safety of ICPS. Deep neural networks have demonstrated competitive results for intelligent fault diagnosis, which are usually trained via the historical data of all fault modes. However, in real engineering, it is usually difficult to collect samples and exhaust all failures during the training stage. As a result, out-of-distribution fault diagnosis (OOD-FD) becomes a more realistic problem that requires the methods to not only accurately diagnose the known faults, but also effectively recognize unknown ones. Therefore, a novel orthogonal anchor clustering with focal attention (FA-OAC) is proposed in this paper for OOD-FD. Firstly, an orthogonal anchor clustering (OAC) algorithm is proposed to fix the class center of each fault mode orthogonally and distinguish the known and unknown faults at the class level. Then, because the identifiability of different fault modes changes a lot in OOD-FD, the focal attention mechanism is applied to dynamically adjust the attention to different fault modes according to the distance loss of OAC, thus addressing the identifiability imbalance problem. To verify the effectiveness of the proposed method, different OOD-FD tasks are designed based on two rotating machinery datasets. The experimental results and comparison with state-of-the-art fault diagnosis methods have demonstrated that the proposed method has improved the OOD-FD performance greatly and therefore provides an effective tool in real engineering. © 2023 IEEE.

关键词： Rotating machinery

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Minimizing Maximum Tardiness in a Distributed Flow Shop Manufacturing Problem under No-Waiting and Sequence Dependent Setup Time Constraints

Minimizing Maximum Tardiness in a Distributed Flow Shop Manu...

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International Conference on Intelligent systems: Theories and Applications (SITA)

作者： Achraf Sayah Said Aqil Mohamed Lahby Laboratory of Applied Mathematics and Computer Sciences Higher Normal School Hassan II University of Casablanca Morocco Laboratory Artificial Intelligence and Complex Systems Engineering National Higher School Of Arts And Crafts Hassan II University of Casablanca Morocco

The distributed no-wait flow-shop manufacturing problem with sequence dependent setup time (DNWFSMP-SDST) is a challenging optimization problem that arises in various industries, including manufacturing and logistics. This problem involves scheduling a set of jobs on multiple machines in a distributed environment, where each job has a specific processing time and requires setup time between different machine transitions. The objective is to minimize the maximum tardiness of all jobs, which represents the maximum delay in completing any job beyond its desired due date. This study addresses the DNWFSMP-SDST optimization problem by employing two algorithms: Nawaz-Enscore-Ham (NEH) and Greedy Randomized Adaptive Search Procedure (GRASP). The NEH is a constructive heuristic that constructs an initial solution by iteratively inserting jobs into a partially ordered sequence. In contrast, GRASP combines a greedy randomized construction phase with a local search procedure to iteratively enhance the initial solution. The simulation study compares NEH and GRASP algorithms for solving DNWFSMP-SDST using bench-marking instance. The results show the pros and cons of each algorithm, helping practitioners make better decisions. Where the NEH algorithm outperform for GRASP technique solving the kind of problem. Overall, this research has enabled us to improve our methods for solving scheduling problems in distributed environments.

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Multi-Pose Fusion for Autonomous Polycrystalline Material Decomposition in Hyperspectral Neutron Tomography

Multi-Pose Fusion for Autonomous Polycrystalline Material De...

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Asilomar Conference on Signals, systems & computers

作者： Diyu Yang Mohammad Samin Nur Chowdhury Shimin Tang Singanallur V. Venkatakrishnan Hassina Z. Bilheux Gregery T. Buzzard Charles A. Bouman School of Electrical and Computer Engineering Purdue University West Lafayette IN USA Neutron Scattering Division Oak Ridge National Laboratory Oak Ridge TN USA Electrical and Engineering Infrastructure Division ORNL Oak Ridge TN USA Department of Mathematics Purdue University West Lafayette IN USA

ISBN: (数字)9798350354058

ISBN: (纸本)9798350354065

Hyperspectral neutron computed tomography (HSnCT) is an effective technique for characterizing poly crystalline material samples. A typical scan involves making multiple HS projection measurements by rotating the sample about a single axis and using a standard algorithm for tomographic reconstruction. Recently, an autonomous polycrystalline material decomposition (APMD) algorithm was proposed to obtain accurate 3D reconstruction of the different materials or crystallographic phases in the object. However, for objects with complex compositions and shapes, using data from a single rotation axis may result in reconstructions with significant noise and inaccuracies in the material decomposition. In this paper, we present a multi-pose reconstruction algorithm to produce a single reconstruction from HSnCT data corresponding to multiple poses of the object. Our algorithm extends previous APMD work to incorporate hyperspectral neutron measurements from multiple poses, utilizing the Multi-Agent Consensus Equilibrium (MACE) framework to integrate projections from different rotation axes into a single reconstruction. We apply our method to simulated data and demonstrate that multi-pose APMD achieves significantly improved material decomposition accuracy compared to single-pose APMD.

关键词： Accuracy Three-dimensional displays Shape Computed tomography Software algorithms Neutrons Software Standards Rotation measurement Hyperspectral imaging

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Bifurcation Analysis of Incompressible Fluid Flow by a High Order Mesh-Free Indicator with Padé Approximants 15th

Bifurcation Analysis of Incompressible Fluid Flow by a Hi...

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15th International Moroccan Congress of Mechanics, CMM 2022

作者： Rammane, M. Mesmoudi, S. Askour, O. Tri, A. Braikat, B. Damil, N. Laboratory of Materials Signals Systems and Physical Modeling Department of Physics Faculty of Sciences Agadir University Ibn Zohr BP 8106 Agadir80000 Morocco Hassan First University of Settat National School of applied Sciences LISA Laboratory Berrechid26100 Morocco Mathematics Computer Science and Communication Systems Laboratory National School of Applied Sciences of Safi Cadi Ayyad University BP 63 Safi Sidi Bouzid46000 Morocco Laboratory of Mechanics Faculty of Sciences Ain Chock Hassan II University of Casablanca Casablanca Morocco Km 7 Route d’El Jadida Casablanca Morocco Laboratory of Engineering and Materials Faculty of Sciences Ben M’sik Hassan II University of Casablanca B.P 7955 Sidi Othman Casablanca Morocco Central Casablanca Complex Systems and Interactions Research Center Green City Bouskoura27182 Morocco

ISBN: (纸本)9783031469725

In this work, a mesh-free indicator is proposed to detect the bifurcation points of incompressible viscous fluid flow in a 2D sudden expansion. This indicator is mainly based on the high order mesh-free algorithm (HO-MFA) to solve the nonlinear problems obtained from the linear stability analysis. The Padé approximants are then used to improve the validity range of the HO-MFA and to determinate the roots of the indicator. The combination of these mathematical tools allows us to determine the zero of the indicator corresponding to the critical point. The Lyapunov-Schmidt reduction is used to search all the bifurcated branches from the critical point. To show the accuracy of our model, comparisons of the obtained results with those of the literature are made. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Linear stability analysis

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Swallowing Assessment using High-Resolution Cervical Auscultations and Transformer-based Neural Networks

Swallowing Assessment using High-Resolution Cervical Auscult...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Ayman Anwar Yassin Khalifa Erin Lucatorto James L. Coyle Ervin Sejdic Department of Electrical and Computer Engineering Faculty of Applied Science & Engineering University of Toronto Toronto Canada Center for Research Computing and Information Technology Analytics University of Pittsburgh Pittsburgh PA USA Systems and Biomedical Engineering Department Faculty of Engineering Cairo University Giza Egypt Department of Communication Science and Disorders School of Health and Rehabilitation Sciences University of Pittsburgh Pittsburgh PA USA Department of Electrical and Computer Engineering Faculty of Applied Science & Engineering University of Toronto and North York General Hospital Toronto Canada

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

Swallowing assessment is a crucial task to reveal swallowing abnormalities. There are multiple modalities to analyze swallowing kinematics, such as videofluoroscopic swallow studies (VFSS), which is the gold standard method, and high-resolution cervical auscultation (HRCA), which is a noninvasive technique that uses a triaxial accelerometer attached to the patient’s neck. Deep learning models play an essential role in data driven analysis of swallowing landmarks using VFSS and/or HRCA as input data. Most of these models utilize convolutional and recurrent neural networks. Here, we investigate the ability of transformers to analyze swallowing kinematics; specifically upper esophageal sphincter opening and laryngeal vestibule closure using HRCA signals. We tested the model using an independent test dataset to assess the generalizability of the proposed network. The proposed network achieved an average detection accuracy higher than 90% and 85% for both segmentation tasks, which outperform the hybrid neural networks from the literature, and the model obtained high-performance measures for the independent dataset, showing the transformers’ ability to generalize on unseen data.

关键词： Accuracy Sensitivity Recurrent neural networks Convolution Kinematics Transformers Feature extraction Solids Data models Signal resolution

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Power-Measurement-Based Channel Autocorrelation Estimation for IRS-Assisted Wideband Communications

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IEEE Transactions on Wireless Communications 2025年第6期24卷 4647-4662页

作者： Sun, He Zhu, Lipeng Mei, Weidong Zhang, Rui National University of Singapore Department of Electrical and Computer Engineering 117583 Singapore University of Electronic Science and Technology of China National Key Laboratory of Wireless Communications 611731 China The Chinese University of Hon g Kong School of Science and Engineering Shenzhen Research Institute of Big Data Guangdong Shenzhen518172 China

Channel state information (CSI) is essential to the performance optimization of intelligent reflecting surface (IRS)-aided wireless communication systems. However, the passive and frequency-flat reflection of IRS, as well as the high-dimensional IRS-reflected channels, have posed practical challenges for efficient IRS channel estimation, especially in wideband communication systems with significant multi-path channel delay spread. To tackle the above challenge, we propose a novel neural network (NN)-empowered IRS channel estimation and passive reflection design framework for the wideband orthogonal frequency division multiplexing (OFDM) communication system based only on the user’s reference signal received power (RSRP) measurements with time-varying random IRS training reflections. As RSRP is readily accessible in existing communication systems, our proposed channel estimation method does not require additional pilot transmission in IRS-aided wideband communication systems. In particular, we show that the average received signal power over all OFDM subcarriers at the user terminal can be represented as the prediction of a single-layer NN composed of multiple subnetworks with the same structure, such that the autocorrelation matrix of the wideband IRS channel can be recovered as their weights via supervised learning. To exploit the potential sparsity of the channel autocorrelation matrix, a progressive training method is proposed by gradually increasing the number of subnetworks until a desired accuracy is achieved, thus reducing the training complexity. Based on the estimates of IRS channel autocorrelation matrix, the IRS passive reflection is then optimized to maximize the average channel power gain over all subcarriers. Numerical results indicate the effectiveness of the proposed IRS channel autocorrelation matrix estimation and passive reflection design under wideband channels, which can achieve significant performance improvement compared to the existing IRS re

关键词： Orthogonal frequency division multiplexing

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A State Feedback Controller for Mitigation of Continuous-Time Networked SIS Epidemics

arXiv

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arXiv 2022年

作者： Wang, Yuan Gracy, Sebin Uribe, César A. Ishii, Hideaki Johansson, Karl Henrik Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology and Digital Futures Stockholm Sweden Department of Electrical and Computer Engineering Rice University HoustonTX United States Department of Computer Science Tokyo Institute of Technology Yokohama Japan

The paper considers continuous-time networked susceptible-infected-susceptible (SIS) diseases spreading over a population. Each agent represents a sub-population and has its own healing rate and infection rate;the state of the agent at a time instant denotes what fraction of the said sub-population is infected with the disease at the said time instant. By taking account of the changes in behaviors of the agents in response to the infection rates in real-time, our goal is to devise a feedback strategy such that the infection level for each agent strictly stays below a pre-specified value. Furthermore, we are also interested in ensuring that the closed-loop system converges either to the disease-free equilibrium or, when it exists, to the endemic equilibrium. The upshot of devising such a strategy is that it allows health administration officials to ensure that there is sufficient capacity in the healthcare system to treat the most severe cases. We demonstrate the effectiveness of our controller via numerical examples. © 2022, CC BY.

关键词： Closed loop systems

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