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DESYNCHRONIZATION OF TWO COUPLED LIMIT-CYCLE OSCILLATORS USING AN ASTROCYTE-INSPIRED CONTROLLER

International Journal of Biomathematics 2014年第1期7卷 1-23页

作者： GHAZAL MONTASERI MOHAMMAD JAVAD YAZDANPANAH Advanced Control Systems Laboratory School of Electrical and Computer EngineeringCollege of Engineering University of Tehran Tehran Iran Advanced Control Systems LaboratoryControl and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran

Astrocytes have potential to break synchrony between neurons. Authors＇ recent researches reveal that astrocytes vary the synchronization threshold and provide an appropriate feedback control in stabilizing neural activities. In this study, we propose an astrocyte-inspired controller for desynchronization of two coupled limit-cycle oscillators as a minimal network model. The design procedure consists of two parts. First, based on the astrocyte model, the structure of the dynamic controller is suggested. Then, to have an emcient controller, parameters of controller are tuned through an optimization algo- rithm. The proposed bio-inspired controller takes advantages of three important proper- ties：（1） the controller desynchronizes the oscillators without any undesirable effects （e.g. stopping, annihilating or starting divergent oscillations）; （2） it consumes little effort to preserve the desirable desynchronized state; and （3） the controller is robust with respect to parameters＇ variations. Simulation results reveal the ability of the proposed controller.

关键词： Astrocyte dynamic model bio-inspired controller coupled limit-cycle oscillators desynchronization optimization

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Predicting the uplift capacity of circular anchors in frictional-cohesive soils using Kolmogorov-Arnold networks

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Scientific Reports 2025年第1期15卷 1-26页

作者： Vu-Hoang, Tran Nguyen, Tan Shiau, Jim Pham-Tran, Hung-Thinh Nguyen-Thoi, Trung Faculty of Civil Engineering Ton Duc Thang University Ho Chi Minh City Viet Nam Smart Computing in Civil Engineering Research Group Faculty of Civil Engineering Ton Duc Thang University Ho Chi Minh City Viet Nam School of Engineering University of Southern Queensland Toowoomba 4350 QLD Australia Laboratory for Applied and Industrial Mathematics Institute for Computational Science and Artificial Intelligence Van Lang University Ho Chi Minh City Viet Nam Faculty of Mechanical-Electrical and Computer Engineering School of Technology Van Lang University Ho Chi Minh City Viet Nam

This study investigates the uplift capacity of circular anchors embedded in frictional-cohesive soils under surcharge. The analysis focuses on three critical stability factors F_c, F_q, and F_γ using Terzaghi’s principle of superposition to evaluate ultimate bearing capacity. These factors are influenced by the soil’s internal friction angle, the geometric ratio of anchor depth to diameter, and the interface roughness between the anchor and soil. Three predictive models for these stability factors are developed using advanced computational methods, including finite element limit analysis (FELA) with adaptive meshing and Kolmogorov-Arnold Networks (KAN). This research is the first to apply KAN in anchor behavior studies, demonstrating its enhanced ability to model complex data relationships compared to artificial neural networks (ANN). Additionally, a closed-form solution for stability factors is derived through KAN, providing an efficient method for predicting bearing capacity. The optimized models exhibit high coefficient of determination (R²) values and low root mean square errors (RMSE) for training and testing datasets. Sensitivity analysis validates the robustness of the proposed models. These findings advance the understanding of circular anchors’ bearing capacity in frictional-cohesive soils, offering practical design insights for various soil conditions. © The Author(s) 2025.

关键词： Closed-form solution Frictional-cohesive soils Kolmogorov-Arnold networks (KAN) Sensitivity analysis Terzaghi stability factors Uplift capacity

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Optimizing Sparse Matrix-Vector Multiplication using index and value compression 08

Optimizing Sparse Matrix-Vector Multiplication using index a...

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2008 Conference on computing Frontiers, CF'08

作者： Kourtis, Kornilios Goumas, Georgios Koziris, Nectarios Computing Systems Laboratory National Technical University of Athens School of Electrical and Computer Engineering Zografou 15780 Greece

ISBN: (纸本)9781605580777

Previous research work has identified memory bandwidth as the main bottleneck of the ubiquitous Sparse Matrix-Vector Multiplication kernel. To attack this problem, we aim at reducing the overall data volume of the algorithm. Typical sparse matrix representation schemes store only the nonzero elements of the matrix and employ additional indexing information to properly iterate over these elements. In this paper we propose two distinct compression methods targeting index and numerical values respectively. We perform a set of experiments on a large real-world matrix set and demonstrate that the index compression method can be applied successfully to a wide range of matrices. Moreover, the value compression method is able to achieve impressive speedups in a more limited yet important class of sparse matrices that contain a small number of distinct values. Copyright 2008 ACM.

关键词： Matrix algebra

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A generalized model of TiOx-based memristive devices and its application for image processing

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Chinese Physics B 2017年第9期26卷 70-81页

作者：张江伟汤振森许诺王耀孙红辉王之元方粮 State Key Laboratory of High Performance Computing National University of Defense Technology School of Computer National University of Defense Technology Department of Electrical and Computer Engineering University of Pittsburgh Department of Material Science and Engineering College of EngineeringSeoul National University School of Computer National University of Defense Technology

Memristive technology has been widely explored, due to its distinctive properties, such as nonvolatility, high density,versatility, and CMOS compatibility. For memristive devices, a general compact model is highly favorable for the realization of its circuits and applications. In this paper, we propose a novel memristive model of TiOx-based devices, which considers the negative differential resistance（NDR） behavior. This model is physics-oriented and passes Linn＇s criteria. It not only exhibits sufficient accuracy（IV characteristics within 1.5% RMS）, lower latency（below half the VTEAM model）,and preferable generality compared to previous models, but also yields more precise predictions of long-term potentiation/depression（LTP/LTD）. Finally, novel methods based on memristive models are proposed for gray sketching and edge detection applications. These methods avoid complex nonlinear functions required by their original counterparts. When the proposed model is utilized in these methods, they achieve increased contrast ratio and accuracy（for gray sketching and edge detection, respectively） compared to the Simmons model. Our results suggest a memristor-based network is a promising candidate to tackle the existing inefficiencies in traditional image processing methods.

关键词： memristor modeling memristor-based network gray sketching edge detection

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Electrochemical Detection of Lactate and Glucose with Enzyme-Free and Dual-Sensing Using Nickel-Oxide Nanoparticles

SSRN

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SSRN 2025年

作者： Nasiri, Rohollah Guagliano, Giuseppe Van Gastel, Dirkje Sanei, Reihaneh Madadelahi, Masoud Tanriverdi, Selim Jain, Saumey Fayazbaksh, Farzaneh Lee, Sang Won Zhu, Yangzhi Joensson, Haakan N. Russom, Aman Herland, Anna Division of Nanobiotechnology Department of Protein Science Science for Life Laboratory KTH Royal Institute of Technology Solna Sweden AIMES Center for the Advancement of Integrated Medical and Engineering Sciences Department of Neuroscience Karolinska Institute Solna Sweden Department of Chemistry Materials and Chemical Engineering "G. Natta" Politecnico di Milano Milan Italy Division of Micro and Nanosystems Department of Intelligent Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Terasaki Institute for Biomedical Innovation Los AngelesCA90064 United States

Detection and monitoring of lactate and glucose levels in biological fluids and cell cultures are critical for understanding metabolic disorders. While electrochemical biosensors are commonly used, traditional enzymatic sensors face stability, reproducibility, and cost challenges. To address these issues, we developed non-enzymatic sensors using nanostructured electrodes, specifically nickel oxide (NiO)-based, for lactate and glucose detection. The sensors were fabricated by drop-casting a NiO/Nafion/ethanol dispersion onto the working electrode, with performance evaluated through cyclic voltammetry and amperometry. Optimal sensitivity and linearity were achieved at a working voltage of ~0.5 V. To address glucose interference, sensors were modified with Prussian Blue, creating a dual sensor for lactate and glucose. The sensors respectively exhibited linear responses for lactate (0.1 – 5 mM) and glucose (0.1 – 5 mM) with detection limits of 0.60 mM and 0.35 mM, and it showed sensitivities of 0.43 ± 0.05 µA/mM (lactate) and 0.82 ± 0.02 µA/mM (glucose) in phosphate buffer solution. Validation against the lactate and glucose assay kits in a cell culture medium showed good agreement, highlighting the potential of these enzyme-free electrochemical sensors for metabolic analysis. Finally, the sensor was integrated with a microfluidic device, demonstrating its potential as a flow-through, enzyme-free metabolic sensor for future organ-on-chip applications. © 2025, The Authors. All rights reserved.

关键词： Cyclic voltammetry

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A Novel Three-Phase Tubular Permanent Magnet Linear Generator for Free-Piston Stirling Engines

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IEEE Transactions on Plasma Science 2025年

作者： Wang, Xing Chen, Hao Liu, Yongqiang Torkaman, Hossein Li, Xiaodong Palka, Ryszard Gu, Jason China University of Mining and Technology School of Electrical Engineering Xuzhou221116 China International Joint Research Center of Central and Eastern European Countries on New Energy Electric Vehicle Technology and Equipment Xuzhou221008 China International Cooperation Joint Laboratory of New Energy Power Generation and Electric Vehicles of Jiangsu Province Colleges and Universities Xuzhou221008 China Jiangsu Province Foreign Expert Workshop on New Energy Power Generation and Electric Transportation Xuzhou221008 China Shahid Beheshti University Faculty of Electrical Engineering Tehran19839 69411 Iran Macau University of Science and Technology Faculty of Information Technology Macau China West Pomeranian University of Technology Department of Power Systems and Electrical Drives Szczecin70-310 Poland Dalhousie University Department of Electrical and Computer Engineering HalifaxNSB3H 4R2 Canada

This article proposes an air-cored three-phase tubular permanent magnet linear generator (3P-TPMLG) with a novel free-piston Stirling engines (FPSEs) structure. First, the concrete construction and initial dimensions of the 3P-TPMLG are given through design principles and experience. Second, the mover’s basic working principle and operational process are discussed using relevant equations and the isolines distribution of magnetic vector potential at several typical mover positions. Third, the 2-D and 3-D machine models established by finite element analysis (FEA) software FLUX and electromagnetic field analysis are presented. Furthermore, two pivotal parameters are optimized to improve operating conditions and output performance of 3P-TPMLG. Finally, the output parameters of 3P-TPMLG are solved separately by FLUX under the constant and sinusoidal velocities. Following finite element dynamic simulation verification, 3P-TPMLG has good power output at both unchanged and sinusoidal velocities. Meanwhile, when the reciprocating frequency is 80 Hz, and the proportion of permanent magnet (PM) length in half pole pitch is 7/10, the comprehensive evaluation of the generator is optimal. The novel structural 3P-TPMLG for FPSEs can realize symmetrical three-phase power generation when the mover reciprocates linear motion at a sinusoidal velocity. Besides, the comparisons prove that the 3P-TPMLG has the advantages of high efficiency, high power generation density, and low construction price. © 1973-2012 IEEE.

关键词： Permanent magnets

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Evaluation of minor labial salivary gland focus score in Sjögren's disease using deep learning: a tool for more efficient diagnosis and future tissue biomarker discovery

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Journal of Autoimmunity 2025年 153卷 103418-103418页

作者： Panagiotopoulos, Konstantinos N. Tsiknakis, Nikos Zaridis, Dimitrios I. Mavragani, Clio P. Tzioufas, Athanasios G. Fotiadis, Dimitrios I. Goules, Andreas V. Department of Pathophysiology and Joint Rheumatology Medical School National and Kapodistrian University of Athens Greece Computational BioMedicine Laboratory Foundation for Research and Technology Hellas Greece Biomedical Research Institute Foundation for Research and Technology Hellas Greece Biomedical Engineering Laboratory School of Electrical & Computer Engineering National Technical University of Athens Greece Unit of Medical Technology and Intelligent Information Systems Department of Materials Science and Engineering University of Ioannina Greece Department of Physiology Medical School National and Kapodistrian University of Athens Greece Department of Oncology Pathology Karolinska Institute Sweden Biomedical Research Foundation of the Academy of Athens Greece Research Institute for Systemic Autoimmune Diseases Greece

Background: Sjögren's Disease (SjD) is histopathologically characterized by focal sialadenitis in minor labial salivary gland biopsies (mLSGB), which is evaluated by utilizing the focus score (FS). Focus score ≥1 identification is a critical step of the diagnostic approach and SjD classification. Nonetheless, during mLSGB analysis, FS reporting is neglected in a staggering 17 %, and a degree of inter-observer variability is introduced, even among specialized university centers. As the unmet need for reliable FS reporting is displayed, leveraging artificial intelligence in mLSGB evaluation shows encouraging potential and mandates to be investigated. Methods: Minor LSGBs stained only with hematoxylin and eosin (H&E) during evaluation of individuals with a clinical suspicion of SjD, were randomly chosen from our archive. All mLSGBs were scanned digitally as whole slide images (WSI) and the final dataset was partitioned into a training (70 %) and a test set (30 %). An attention-based deep learning binary classification model was employed for evaluation of mLSGBs positivity (FS ≥ 1 or FS < 1). Results: The final dataset consisted of 271 mLSGBs, with 153 (56 %) having FS < 1 and 118 (44 %) FS ≥ 1. In the FS ≥ 1 subset, 74 (63 %) were in the FS = 1–2 range, and the remaining biopsies had FS > 2, following the expected FS distribution among the typical SjD population. Our model resulted in: AUC = 0.932 (0.881–0.984), sensitivity 87 % (0.733–0.944), specificity 84 % (0.71–0.915) and accuracy 85.2 % (0.763–0.912), achieving better performance from previous works. Conclusion: Artificial intelligence models may overcome the intra-observer biases and inter-observer variability in FS evaluation, reinforcing the diagnosis and biomarker discovery in SjD. © 2025 Elsevier Ltd

关键词： Artificial intelligence Deep learning Focus score Lip biopsy Rheumatology Sjogren syndrome Sjögren's disease

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Macro liveness graph and liveness of ω-independent unbounded nets

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Science China(Information Sciences) 2015年第3期58卷 132-141页

作者： WANG ShouGuang GAN MengDi ZHOU MengChu School of Information and Electronic Engineering Zhejiang Gongshang University Key Laboratory of Embedded System and Service Computing Ministry of EducationTongji University Department of Electrical and Computer Engineering New Jersey Institute of Technology

Liveness is a basic property of a system and the liveness issue of unbounded Petri nets remains one of the most difficult problems in this *** work proposes a novel method to decide the liveness of a class of unbounded generalized Petri nets calledω-independent unbounded nets,breaking the existing limits to one-place-unbounded *** algorithm to construct a macro liveness graph(MLG)is developed and a critical condition based on MLG deciding the liveness ofω-independent unbounded nets is *** are provided to demonstrate its effectiveness.

关键词： discrete event system(DES) Petri nets complex systems liveness property analysis

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Implicit Multi-Scale Swin Transformer Network for Image Denoising

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IEEE Transactions on Consumer Electronics 2025年

作者： Zhang, Qi Ding, Yuwei Zhang, Weiqi Zhu, Yian Zhang, Bob Lin, Jerry Chun-Wei Harbin Institute of Technology at Weihai School of Economics and Management Weihai China Nanjing University State Key Laboratory for Novel Software Technology Nanjing China Northwestern Polytechnical University School of Computer Science Xi’an China Northwestern Polytechnical University Yangtze River Delta Research Institute Taicang China University of Macau PAMI Research Group Department of Computer and Information Science Taipa China Department of Distributed Systems and IT Devices Electrical Engineering and Mathematical Sciences Silesian university of technology Poland

Image denoising has been used in various edge computing scenarios such as consumer electronics to improve the image quality and user experience. Existing image denoising methods based on Convolutional Neural Networks (CNNs) and vision Transformers achieve good performance by empirically utilizing residual neural network (ResNet) as basic component. However, ResNet lacks interpretability in network design and also long-term memory of features, potentially restricting the performance of denoising networks. In this paper, we propose an Implicit Multi-scale Swin Transformer Network (IMSNet) for image denoising, which introduces the implicit Euler scheme from the feature memory perspective. Specifically, densely connected implicit feature extraction blocks (IFEBs) are designed to learn the residual mapping between noisy and clean images. The IFEB reformulates the initial skip connection of ResNet based on the implicit Euler discretization, providing both network interpretability and long-term memory. In IFEB, the multi-scale swin Transformer block (MSB) is designed as the implicit layer to capture spatial details and non-local contextual information at different scales. Additionally, a cross-layer feature fusion block (CLFF) is proposed to further improve feature reuse capabilities. Compared to existing denoising networks, the extensive experiments demonstrate the superior performance of our IMSNet in various image denoising tasks, and the flexibility in the practical applications with proposed light model on resource-restricted platforms such as consumer electronic devices. © 1975-2011 IEEE.

关键词： Image denoising

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Authors' Reply

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IEEE Sensors Journal 2018年第3期18卷 1336-1337页

作者： Ghanbari, Milad Yazdanpanah, Mohammad Javad School of Electrical and Computer Engineering University of Tehran Tehran*** Iran Control and Intelligent Processing Center of Excellence Advanced Control Systems Laboratory College of Engineering School of Electrical and Computer Engineering University of Tehran Tehran*** Iran

The experimental results of the paper titled 'Delay compensation of tilt sensors based on mems accelerometer using data fusion technique' was commented by Bodnicki and Luczak. In this note, we address the raised comments by the mentioned authors. Moreover, appropriate explanations are provided in order to make the procedure of the experimental section more clear. © 2001-2012 IEEE.

关键词： Kalman filters

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