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作者： Ashrafzadeh, Behnam Zaimbashi, Amir Soleimani-Nasab, Ehsan Uysal, Murat Department of Electrical Engineering Optical and Rf Communication Systems Laboratory Shahid Bahonar University of Kerman Kerman*** Iran Department of Electrical and Computer Engineering Graduate University of Advanced Technology Kerman*** Iran Department of Electrical and Electronics Engineering Özyegin University Istanbul34794 Turkey

Free space optical (FSO) communication systems provide high bandwidth in unregulated spectrum and act as a powerful line-of-sight wireless connectivity solution. The performance of FSO systems can be seriously impaired by fading as a result of atmospheric turbulence and/or pointing errors due to misalignment. In the context of FSO systems, relaying was proposed as an effective fading mitigation technique due to the fact that the variance is distance-dependent in turbulence channels. In this article, we present a unified performance analysis of multi-hop FSO systems over Double Generalized Gamma (DGG) turbulence channels with pointing error impairments. We assume amplify-and-forward relaying and consider both heterodyne detection and intensity modulation with direct detection. We derive tight closed-form expressions for the outage probability and bit error probability of both fixed-gain and channel state information (CSI)-assisted relaying in terms of the bivariate Fox-H functions and Fox-H functions, respectively. We further analyze asymptotic behavior of the outage probability in terms of simple elementary functions and obtain the achievable diversity orders. Diversity gain is found to be a function of atmospheric turbulence parameters, pointing error, detection type and the number of hops. Monte Carlo simulation results are further provided to verify the accuracy of the derived expressions. © 2002-2012 IEEE.

关键词： Atmospheric turbulence

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Graphene-based silicon modulators

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Frontiers of Information Technology & Electronic engineering 2019年第4期20卷 458-471页

作者： Hao-wen SHU Ming JIN Yuan-sheng TAO Xing-jun WANG State Key Laboratory on Advanced Optical Communication Systems and Networks Department of ElectronicsSchool of Electronics Engineering and Computer Science Peking University Nano-optoelectronics Frontier Center of Ministry of Education at Peking University

Silicon photonics is a promising technology to address the demand for dense and integrated nextgeneration optical interconnections due to its complementary-metal-oxide-semiconductor(CMOS) ***, one of the key building blocks, the silicon modulator, suffers from several drawbacks, including a limited bandwidth, a relatively large footprint, and high power consumption. The graphene-based silicon modulator, which benefits from the excellent optical properties of the two-dimensional graphene material with its unique band structure,has significantly advanced the above critical figures of merit. In this work, we review the state-of-the-art graphenebased silicon modulators operating in various mechanisms, i.e., thermal-optical, electro-optical, and plasmonic. It is shown that graphene-based silicon modulators possess the potential to have satisfactory characteristics in intra-and inter-chip connections.

关键词： Silicon photonics Graphene Optical modulator

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Low-Cost, High Sensitivity Paper-Based Bacteria Impedance Sensor Based on Vertical Flow Assay

SSRN

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SSRN 2022年

作者： Long, Yifan Ai, Zhehong Zhang, Longhan Zhang, Han Jiang, Jing Logan, G. Liu Research Center for Intelligent Sensing Systems Zhejiang Laboratory Zhejiang Hangzhou311100 China Hangzhou Institute for Advanced Study University of Chinese Academy of Sciences Zhejiang Hangzhou310024 China Department of Electrical & Computer Engineering the University of Illinois at Urbana-Champaign UrbanaIL61801 United States

This study proposed a low-cost, portable paper-fluidic vertical flow assay bacteria counter at high accuracy. We designed the sensor at a low fabrication cost based on e-beam evaporation and 3D printing based on the impedance measurement principle. Interdigitated (IDT) electrodes were coated on the filter membrane by e-beam evaporation with a shadow mask. We could print wafer-scale frames with low-melting temperature 3D printing material to confine liquid bacteria samples within the IDT sensing region. This novel fabrication technique significantly reduced the chip cost to less than 1% of silicon-based chips. Two equivalent circuit models were proposed for different concentration ranges to analyze the principle of paper-based impedance bacteria sensors. We proposed an "improved model" based on the Randles model for low concentration by considering the leaky double layer capacitor effect and spherical diffusion from nano-structural electrodes of the gold-coated filter membrane. The hook effect was found and explained at a high concentration range by the pearl chain effect. We modeled the pearl chain effect as a pair of RC parallel to the low concentration model. When users apply both models properly for analysis, this sensor could quantitatively measure cell concentrations from 40 to 400M per milliliter with superior linearity. © 2022, The Authors. All rights reserved.

关键词： Bacteria

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Soft yet Effective Robots via Holistic Co-Design

arXiv

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arXiv 2025年

作者： Stölzle, Maximilian Pagliarani, Niccolò Stella, Francesco Hughes, Josie Laschi, Cecilia Rus, Daniela Cianchetti, Matteo Santina, Cosimo Della Zardini, Gioele Laboratory for Information & Decision Systems Massachusetts Institute of Technology CambridgeMA02139 United States Cognitive Robotics Delft University of Technology Mekelweg 2 CD Delft2628 Netherlands The BioRobotics Institute Scuola Superiore Sant’Anna Pisa56025 Italy Embodied AI AG Lausanne1015 Switzerland CREATE Lab EPFL Lausanne1015 Switzerland Advanced Robotics Centre Department of Mechanical Engineering National University of Singapore 117575 Singapore Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology CambridgeMA02139 United States

Soft robots promise inherent safety via their material compliance for seamless interactions with humans or delicate environments. Yet, their development is challenging because it requires integrating materials, geometry, actuation, and autonomy into complex mechatronic systems. Despite progress, the field struggles to balance task-specific performance with broader factors like durability and manufacturability—a difficulty that we find is compounded by traditional sequential design processes with their lack of feedback loops. In this perspective, we review emerging co-design approaches that simultaneously optimize the body and brain, enabling the discovery of unconventional designs highly tailored to the given tasks. We then identify three key shortcomings that limit the broader adoption of such co-design methods within the soft robotics domain. First, many rely on simulation-based evaluations focusing on a single metric, while real-world designs must satisfy diverse criteria. Second, current methods emphasize computational modeling without ensuring feasible realization, risking sim-to-real performance gaps. Third, high computational demands limit the exploration of the complete design space. Finally, we propose a holistic co-design framework that addresses these challenges by incorporating a broader range of design values, integrating real-world prototyping to refine evaluations, and boosting efficiency through surrogate metrics and model-based control strategies. This holistic framework, by simultaneously optimizing functionality, durability, and manufacturability, has the potential to enhance reliability and foster broader acceptance of soft robotics, transforming human-robot interactions. © 2025, CC BY.

关键词： Intellectual property core

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Coalition Formation of Microgrids with Distributed Energy Resources and Energy Storage in Energy Market

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Journal of Modern Power systems and Clean Energy 2020年第5期8卷 906-918页

作者： Jaber Valinejad Mousa Marzband Mert Korkali Yijun Xu Ameena Saad Al-Sumaiti IEEE Bradley Department of Electrical and Computer Engineering Virginia TechNorthern Virginia CenterGreater Washington D.C.VA 22043USA Department of Computer Science Virginia TechNorthern Virginia CenterGreater Washington D.C.VA 22043USA Department of Mathematics Physicsand Electrical EngineeringNorthumbria UniversityNewcastleUK Center of Research Excellence in Renewable Energy and Power Systems King Abdulaziz UniversityJeddah 21589Saudi Arabia Computational Engineering Division Lawrence Livermore National LaboratoryLivermoreCA 94550USA Advanced Power and Energy Center Electrical Engineering and Computer ScienceKhalifa UniversityAbu DhabiP.O.Box 127788UAE

Power grids include entities such as home-microgrids(H-MGs),consumers,and retailers,each of which has a unique and sometimes contradictory objective compared with others while exchanging electricity and heat with other ***,there is the need for a smart structure to handle the new *** paper proposes a bilevel hierarchical structure for designing and planning distributed energy resources(DERs)and energy storage in H-MGs by considering the demand response(DR).In general,the upper-level structure is based on H-MG generation competition to maximize their individual and/or group income in the process of forming a coalition with other *** upper-level problem is decomposed into a set of low-level market clearing *** electricity and heat markets are simultaneously modeled in this ***,including wind turbines(WTs),combined heat and power(CHP)systems,electric boilers(EBs),electric heat pumps(EHPs),and electric energy storage systems,participate in the electricity *** addition,CHP systems,gas boilers(GBs),EBs,EHPs,solar thermal panels,and thermal energy storage systems participate in the heat *** show that the formation of a coalition among H-MGs present in one grid will not only have a significant effect on programming and regulating the value of the power generated by the generation resources,but also impact the demand consumption and behavior of consumers participating in the DR program with a cheaper market clearing price.

关键词： Microgrids distributed energy resource(DER) electricity market heat market demand response(DR) coalition formation energy storage

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Super-Robust Nonadiabatic Holonomic Quantum Computation in coherence-protected Superconducting Circuits

arXiv

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arXiv 2024年

作者： Wang, Yuan-Sheng Su, Zhaofeng Chen, Xiaosong Yung, Man-Hong School of Systems Science Beijing Normal University Beijing100875 China School of Electronics and Information Engineering Suzhou Vocational University Suzhou215104 China School of Computer Science and Technology University of Science and Technology of China Hefei230094 China CAS Key Laboratory of Wireless-Optical Communications University of Science and Technology of China Hefei230026 China Institute for Advanced Study in Physics School of Physics Zhejiang University Hangzhou310058 China Shenzhen Institute for Quantum Science and Engineering Southern University of Science and Technology Shenzhen518055 China International Quantum Academy Shenzhen518048 China Guangdong Provincial Key Laboratory of Quantum Science and Engineering Southern University of Science and Technology Shenzhen518055 China Shenzhen Key Laboratory of Quantum Science and Engineering Southern University of Science and Technology Shenzhen518055 China

The schmeme of nonadiabatic holonomic quantum computation (NHQC) offers an error-resistant method for implementing quantum gates, capable of mitigating certain errors. However, the conventional NHQC schemes often entail longer operations concerning standard gate operations, making them more vulnerable to the effects of quantum decoherence. In this research, we propose an implementation of the Super-Robust NHQC scheme within the Decoherence-Free Subspace (DFS). SR-NHQC has demonstrated robustness against Global Control Errors (GCEs). By utilizing capacitance-coupled transmon qubits within a DFS, our approach enables universal gate operations on a scalable two-dimensional square lattice of superconducting qubits. Numerical simulations demonstrate the practicality of SR-NHQC in DFS, showcasing its superiority in mitigating GCEs and decoherence effects compared to conventional NHQC schemes. Our work presents a promising strategy for advancing the reliability of quantum computation in real-world applications. Copyright © 2024, The Authors. All rights reserved.

关键词： Qubits

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A Machine Learning Model Using Snapshot Ensemble Approach for Soil Respiration Prediction for an Experimental Oak Forest

SSRN

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SSRN 2024年

作者： Ferdous, Syeda Nyma Ahire, Jayendra Pandit Bergman, Richard Li, Xin Blanc-Betes, Elena Zhang, Zhou Wang, Jinxin Lane Department of Computer Science and Electrical Engineering West Virginia University MorgantownWV26505 United States Biological Systems Engineering Department University of Wisconsin MadisonWI53706 United States Forest Products Laboratory USDA Forest Service MadisonWI53726 United States Department of Computer Science University at Albany New YorkNY12222 United States Institute for Sustainability Energy and Environment University of Illinois at Urbana-Champaign UrbanaIL61801 United States Center for Advanced Bioenergy and Bioproducts Innovation University of Illinois at Urbana-Champaign UrbanaIL61801 United States Biological Systems Engineering University of Wisconsin MadisonWI53706 United States Davis Michael Professor of Forestry and Natural Resources West Virginia University MorgantownWV26506 United States

Soil respiration plays a key role in regulating ecosystem CO2 emissions and atmospheric concentrations yet, subject to a strong sensitivity to the environment and large temporal and spatial variability, its contribution to the global carbon cycle remains highly uncertain. Recent advances in ecosystem process-based models have provided unique means to constrain soil respiration rates largely based on learnings from the tracing of ecosystem CO2 losses with radio and stable isotope approaches. However, the computational requirements of process-based models at large scales are costly, limiting their application and predicting capability. With high computational power for the assimilation of high-throughput data to identify patterns and trends in soil respiration and guide in deployment of effective strategies to reduce GHG emission, the application of ML models can help reduce requirement of intensive computational capacity and time for model development and improve the accuracy of predictions. Here, we developed a novel machine learning model that integrated hybrid Prophet-ANN and snapshot ensemble approach. The developed model can be employed as a surrogate of the ForCent model for the Oak Ridge National laboratory deciduous forest. Our proposed model accurately predicted soil CO2 flux with a higher coefficient of determination (R2 > 0.99) for the studied site. We show the potential of our proposed ML model to significantly improve soil CO2 flux predictions which in turn can help us develop more effective strategies for managing soil carbon. © 2024, The Authors. All rights reserved.

关键词： Ecosystems

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FluxProg 2.0 - Teaching Introductory Programming Using Flowcharts with Real and Simulated Robots for The Brazilian Robotics Olympiad (OBR)

FluxProg 2.0 - Teaching Introductory Programming Using Flowc...

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IEEE Latin American Robotics Symposium, LARS

作者： João Alberto Fabro Matheus Biscaya Gutierrez Fernando Henrique Ratusznei Caetano DAINF - Academic Department of Informatica PPGCA - Graduate Program on Applied Computing LASER-Laboratory for Advanced Robotics and Embedded Systems UTFPR - Federal University of Technology - Paraná Curitiba PR - Brazil Information Systems academic - UTFPR - Federal University of Technology - Paraná Curitiba PR - Brazil Computer Engineering academic - UTFPR - Federal University of Technology - Paraná Curitiba PR - Brazil

ISBN: (数字)9781665462808

ISBN: (纸本)9781665462815

In this paper, an approach to aid in introductory programming courses is presented, focused on students that had never had any contact with computer programming. The approach, that was introduced in a previous paper [3], presents programming concepts using icons and “flowcharts”, and a 3D robotics simulator (CoppeliaSim), that has free educational use. This time, a real version of the simulated robot, built using Arduino and cheap, easily obtainable electronic components, is also presented. The programs to control the robot are developed by graphically constructing flowcharts on the visual editor, and then following the execution of programs using the simulated (or real) robot, step by step. This graphic program editor is named “FluxProg”, and its 2nd version is now available online, with new features comprising variables, arithmetic and logic expressions, thus providing a complete programming environment.

关键词： Flowcharts Visualization Three-dimensional displays Conferences Education Electronic components Robots

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CEBRA Method: Decoding Brain Activity for advanced Brain-computer Interface Technology

CEBRA Method: Decoding Brain Activity for Advanced Brain-Com...

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

作者： Jingcheng Yang Frank Kulwa Xuanwei Liu Yiqing Lu Yufa Fu Guanglin Li Yaping Huai Xin Zhang Yongcheng Li CAS Key Laboratory of Human-Machine Intelligence Synergy Systems Shenzhen Institute of Advanced Technology Chinese Academy of Sciences (CAS) Shenzhen China Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming China Shenzhen College of Advanced Technology University of Chinese Academy of Sciences Shenzhen China Shenzhen Dapeng New District Nanao People’s Hospital Shenzhen China Department of Rehabilitation Medicine Shenzhen Longhua District Central Hospital Shenzhen China Brain Cognition and Brain-Computer Intelligence Integration Group Kunming University of Science and Technology Kunming China Shandong Zhongke Advanced Technology Co. Ltd. Jinan China

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

The emerging neurorehabilitation technology, Brain-computer Interface (BCI), provides a novel prospect for stroke recovery. However, decoding brain activity during the movement present substantial challenges, and feature extraction is crutial to build a better decoder. In this study the CEBRA method were employed to extract features first based on electroencephalogram(EEG) data during Motor Execution(ME) and Motor lmagery (Ml) tasks for 20 participants (including 10 stroke patients). The results revealed that, in MI tasks, CEBRA-RF (Random Forests) achieved an average classification accuracy of 91.33%, with an average F1-score of 91.19%, and CEBRA-SVM (Support Vector Machine) achieved an average classification accuracy of 91.32%, with an average F1-score of 90.83%. Compared to other conventional feature extraction methods, CEBRA shows significantly higher accuracy (t-test, p<0.01). However, in ME tasks, CEBRA-RF achieved an average classification accuracy of 75.67%, with an average F1-score of 75.39%, and CEBRA-SVM achieved an average classification accuracy of 76.13%, with an average F1-score of 75.80%. Nevertheless, no significant differences were observed compared to other feature extraction methods. These findings demonstrate the potential of CEBRA in decoding patients’ brain activity. The results of this study hold promise in addressing the current challenges of low decoding accuracy in BCI systems, offering a new approach for designing BCI-assisted rehabilitation systems for stroke patients.

关键词： Support vector machines Brain Accuracy Stroke (medical condition) Feature extraction Motors Brain-computer interfaces Neurorehabilitation Decoding Paralysis

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Global Stability and Optimal Control of Epidemics in Heterogeneously Structured Populations Exhibiting Adaptive Behaviour

SSRN

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SSRN 2023年

作者： Liu, Lixiang Chen, Shanshan Small, Michael Moore, Jack Murdoch Shang, Keke Department of Computer Science School of Electronic and Electrical Engineering Shanghai University of Engineering Science Shanghai201620 China Complex Systems Group Department of Mathematics and Statistics The University of Western Australia Perth6009 Australia Mineral Resources Commonwealth Scientific and Industrial Research Organisation Kensington6151 Australia MOE Key Laboratory of Advanced Micro-Structured Materials School of Physics Science and Engineering Tongji University Shanghai200092 China Computational Communication Collaboratory Nanjing University Nanjing210093 China

During the outbreak of infectious diseases, individual always make some adaptive response to avoid infected the diseases. In this paper, we introduce SIRS model on scale-free networks that take into account behavioral memory and time delay to depict individuals’ adaptive feedback, which is better characterize the actual spread of epidemics. We address uniform persistence and find that the model has the sharp threshold property, that is, for the basic reproduction number less than one, the disease-free equilibrium is globally asymptotically stable, while for the basic reproduction number is above one, the endemic equilibrium is globally stable. We further analyze the effects of two control strategies (the vaccination of susceptible people and treatment of infected people) on epidemic dynamics by optimal control strategy. The existence and uniqueness of the optimal control strategy are obtained. Finally, we perform some stochastic network simulations that yield quantitative agreement with the deterministic mean-field approach. The final results show that the effect of time delay does not change the basic reproduction number, but it plays an important role in the process of disease transmission. The behavioral memory is able to affect the basic reproduction number, and it has important and positive implications for disease transmission and control. The work of this paper can provide a theoretical basis and reference for the prediction and prevention of infectious diseases. © 2023, The Authors. All rights reserved.

关键词： Diseases

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