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Midwest Symposium on Circuits and Systems (MWSCAS)

作者： Marcus Mellor James E. Stine Electrical and Computer Engineering Department VLSI Computer Architecture Research Laboratory Oklahoma State University Stillwater OK USA

ISBN: (数字)9798350387179

ISBN: (纸本)9798350387186

With the current rise in popularity of open source silicon design there is a need for low-cost high-quality SoC design tools. This paper presents an open-source python-based standard cell library char-acterizer compatible with combinational and sequen-tial cells. This characterizer can be configured from a single YAML file, reducing the complexity of the char-acterization process for silicon designers and enabling repeatable characterization through easy integration with existing version control tools. The characterizer generates a liberty file for the cell library that can be used by other EDA tools. The tool is compared to a com-mercial characterizer using an open-source PDK. Timing results are within 1 nanosecond mean absolute er-ror compared to commercial characterization tools.

关键词： Micrometers Accuracy Circuits and systems Process control Libraries Silicon Design tools

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Understanding the Impact of Unobservable Variables on the Performance of Predictive Models: The Need for Feature Space Partitioning and Fusion

Understanding the Impact of Unobservable Variables on the Pe...

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AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Juarez Garcia, Ezequiel Stephens, Chad L. Napoli, Nicholas J. Laboratory Department of Electrical and Computer Engineering University of Florida GainesvilleFL32611 United States Crew Systems & Aviation Operations Branch and System-Wide Safety Project NASA Langley Research Center HamptonVA23681 United States

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

When developing predictive models over a dataset, the model is globally optimized across the entire feature space to learn a decision boundary. However, when unobservable variables—which cannot be measured or estimated—interact with the observable variables, this can negatively impact the optimization applied to the decision boundary since the data samples introduced by unobservable variables may have little to no association with the applied global optimization. This, consequently, penalizes the entire decision boundary and model performance. This paper examines some of the detrimental effects of unobservable variables, particularly their role in creating new modes in the distribution of observable variables and reducing the separ ability of class distributions. Such challenges result in unrepresentative training data, complex skewedor warped decision boundaries, and decreased accuracy of model predictions, particularly for interpretable models like logistic regression and decision trees. Through two illustrative case examples, we highlight the need to address the challenges imposed by unobservable variables. We propose a strategy to mitigate these challenges by creating local regions with in the feature space through partitioning. This enables the optimization of local models with inthe regions to overcome the impact of un observ ability and complex decision boundaries indifferent feature space localities. research into a more sophisticated partitioning strategy and where the partition should be relative to the sample of interest is left as future work. Through the analysis of the impact of un observability and the development of a partitioning method, we demonstrate the clear need for a partitioning strategy that integrates knowledge from multiple local models to estimate risk factors using information fusion. Thus, we establish the foundation and motivation for using partitioning and information fusion to overcome the effects of unobserv ability in predictive mo

关键词： Information fusion

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Coverage analysis and handover strategy in RF/VLC heterogeneous networks

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Applied Optics 2025年第15期64卷 4160-4173页

作者： Feng, Renhai Guo, Yatong Yousaf, Muhammad Zain Khan, Baseem Luo, Liping School of Electrical and Information Engineering Tianjin University Tianjin300072 China School of Physics and Electronic Engineering Xinjiang Normal University Ürümqi830054 China Center for Renewable Energy and Microgrids Huanjiang Laboratory Zhejiang University Zhejiang Zhuji311816 China School of Electrical and Information Engineering Hubei University of Automotive Technology Shiyan China School of Aeronautics and Astronautics Zhejiang University Hangzhou310027 China Department of Electrical and Computer Engineering Hawassa University Hawassa Ethiopia School of Electronics and Information Guangxi Minzu University Nanning530006 China Guangxi Colleges Universities Engineering Research Center for Multi-modal Information Intelligent Sensing Processing and Application Nanning530006 China

Coverage analysis in heterogeneous networks (HetNets) remains insufficient, especially under user mobility and diverse association strategies. To address this, this paper proposes a contact probability and coverage approximation based on association strategy (CPCA-AS) to analyze the coverage probability (CPr) in visible light communication (VLC) and radio frequency (RF) HetNets. Based on the proposed stochastic geometry framework, CPCA-AS evaluates coverage performance under various configurations, including RF-only, VLC-only, and hybrid RF/VLC scenarios. The model incorporates a contact probability mechanism and considers two strategies: opportunistic VLC and maximum received signal power (MRSP). For VLC networks, CPCA-AS utilizes the Gil-Pelaez inversion theorem, and Laplace transforms to efficiently approximate CPr. For RF networks, Markov and Gamma inequalities form conservative accurate approximations and lower bounds. CPCA-AS effectively captures the influence of the photodetector’s field-of-view (FoV) on interference and association behavior. Monte Carlo simulations validate the accuracy of the CPCA-AS. Results demonstrate that CPCA-AS improves CPr. The opportunistic VLC strategy performs better in high-interference and large FoV scenarios. In contrast, the MRSP strategy is more effective in low-interference and low-rate environments. © 2025 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.

关键词： Markov processes

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The ideal PGGAN for the 3D medical data Segmenting

The ideal PGGAN for the 3D medical data Segmenting

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International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)

作者： Nabila Elloumi Hassene Seddik Computer Engineering Department University of Carthage Tunisia Electrical engineering University of Tunis RIFTSI Research Laboratory Tunis Tunisia RIFTSI Research Laboratory Electrical engineering University of Tunis Tunisia Tunis Tunisia

ISBN: (数字)9798350351484

ISBN: (纸本)9798350351491

The radiography is the first pathological examination carried out the diagnosing lung cancer. A deep convolutional neural network (DCNN) was used in the earlier study to automatically categorize DICOM images (Digital Imaging and Communications in Medicine) with cancer features, and able to attain a 95% accuracy rate. More images must be used to train the network in order to increase DCNN performance. Nevertheless, obtaining imagery with multiple attributes through extensive human annotation is challenging. Thus, the purpose of this study is to employ generative adversarial networks (GANs) to increase the classification accuracy of a DCNN using real and synthetic images. Patch depicts were produced from a DICOM image using the suggested technique. As a result, these used a GAN to produce numerous more images that were comparable. In this work, the researchers provide progressive growing of GANs (PGGAN), a technique that makes it possible to produce images with high resolution. By using these images, we were able to pretrain a DCNN. Then, using real patch imagery, the DCNN was adjusted further. In order to verify the efficacy of the suggested approach, we initially assessed the caliber of the images produced by PGGAN and a traditional deep convolutional GAN. Subsequently, we assessed the tumor’s classification performance and verified that the produced depict exhibited similar characteristics to the original images. As a result, we found that the total classification accuracy of lung tumor was 99.48%, an improvement of roughly 4.48% over a trial that was carried out earlier without pretraining using images generated by GANs. These findings allowed us to verify that our suggested approach would successfully classify imagery in situations when only a big data surpassing other methods when the proposed algorithm is tested on actual data from the Salah Azaiez Institute.

关键词： Image segmentation Solid modeling Three-dimensional displays Accuracy Computed tomography Lung Generative adversarial networks

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Analysis of Electro-Magnetic Interference on Underground Cable According to Grounding Methods in AC/DC Hybrid Distribution Networks

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Transactions of the Korean Institute of electrical Engineers 2025年第5期74卷 784-792页

作者： Kwon, Oh-Seung Song, Jin-Sol Kang, Sung-Man Kim, Wook-Won Kim, Chul-Hwan Department of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of Electrical Environment Research Center Korea Electrotechnology Research Institute Korea Republic of Smart Power Distribution Laboratory KEPCO Research Institute Daejeon Korea Republic of

Due to the proportion of renewable energy increase, DC systems are in demand and the study on AC/DC Hybrid system is ongoing. The current AC distribution system is characterized by a passive, unidirectional flow of power, which limits power control and causes power loss in AC/DC conversion for DC demands. The AC/DC Hybrid distribution system improves system operational efficiency by integrating DC systems into existing AC system, expanding the capacity for renewable energy integration, and reducing conversion losses from AC to DC. However, depending on the line configuration, AC/DC cables may be positioned adjacently, potentially causing electro-magnetic interference (EMI) between them. This paper proposes the best grounding methods of underground cable which is appropriate to the AC/DC Hybrid distribution system. The validation of the grounding methods of underground cable was performed by Electro-Magnetic Transients Program (EMTP) ATP-Draw. Copyright © The Korean Institute of electrical Engineers.

关键词： DC distribution systems

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Modular Extremely Large-Scale Array Communication:Near-Field Modelling and Performance Analysis

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China Communications 2023年第4期20卷 132-152页

作者： Xinrui Li Haiquan Lu Yong Zeng Shi Jin Rui Zhang National Mobile Communications Research Laboratory Frontiers Science Center for Mobile Information Communication and SecuritySoutheast UniversityNanjing 210096China Purple Mountain Laboratories Nanjing 211111China The Chinese University of Hong Kong Shenzhen Research Institute of Big DataShenzhen 518172China Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore

This paper investigates the wireless communication with a novel architecture of antenna arrays,termed modular extremely large-scale array(XLarray),where array elements of an extremely large number/size are regularly mounted on a shared platform with both horizontally and vertically interlaced *** module consists of a moderate/flexible number of array elements with the inter-element distance typically in the order of the signal wavelength,while different modules are separated by the relatively large inter-module distance for convenience of practical *** accurately modelling the signal amplitudes and phases,as well as projected apertures across all modular elements,we analyse the near-field signal-to-noise ratio(SNR)performance for modular XL-array *** on the non-uniform spherical wave(NUSW)modelling,the closed-form SNR expression is derived in terms of key system parameters,such as the overall modular array size,distances of adjacent modules along all dimensions,and the user's three-dimensional(3D)*** addition,with the number of modules in different dimensions increasing infinitely,the asymptotic SNR scaling laws are ***,we show that our proposed near-field modelling and performance analysis include the results for existing array architectures/modelling as special cases,e.g.,the collocated XL-array architecture,the uniform plane wave(UPW)based far-field modelling,and the modular extremely large-scale uniform linear array(XL-ULA)of *** simulation results are presented to validate our findings.

关键词： modular extremely large-scale array practical deployment projected apertures non-uniform spherical wave near-field modelling

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NS3-Based Communication Network Modeling for Multi-Microgrid Systems: Design and Evaluation

NS3-Based Communication Network Modeling for Multi-Microgrid...

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IEEE Green Technologies Conference (IEEE-Green)

作者： Ola Ali Osama A. Mohammed Department of Electrical and Computer Engineering Energy Systems Research Laboratory Florida International University Miami FL USA

ISBN: (数字)9798331520182

ISBN: (纸本)9798331520199

This paper presents a communication emulation model for enhancing the efficiency of multi-microgrid (MMG) networks, employing Network Simulator 3 (ns3). MMG systems require robust communication frameworks for coordination, particularly under varying traffic conditions. The introduced model accommodates multiple local area networks (LANs) that support efficient communication across multiple autonomous AC microgrids. The developed model facilitates seamless bidirectional information exchange between the microgrids' local controllers and the MMG control center (MMGCC), employing TCP/IP protocol to ensure high data transmission integrity and low latency. A detailed design in C++ is demonstrated, including the configuration of the communication nodes, topology, communication links, and quality of service (QoS) analysis. The network performance is rigorously assessed across low and high traffic conditions, with performance metrics such as throughput, delay, and percentage packet loss at each node. Results confirm the effectiveness of the introduced model in sustaining minimal packet loss, high throughput, and low delays under dynamic operating scenarios. These findings establish the developed model as a viable solution for meeting the real-time communication requirements of MMG energy management systems.

关键词： Emulation Packet loss TCPIP Quality of service Microgrids C++ languages Throughput Real-time systems Delays Load modeling

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Beamspace Channel Estimation for Wideband Millimeter-Wave MIMO: A Model-Driven Unsupervised Learning Approach

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IEEE Transactions on Wireless Communications 2023年第3期22卷 1808-1822页

作者： He, Hengtao Wang, Rui Jin, Weijie Jin, Shi Wen, Chao-Kai Li, Geoffrey Ye Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Hong Kong Hong Kong The Hong Kong Polytechnic University Department of Electronic and Information Engineering Hong Kong Hong Kong Imperial College London Department of Electrical and Electronic Engineering LondonSW7 2BX United Kingdom Southeast University National Mobile Communications Research Laboratory Nanjing210096 China

Millimeter-wave (mmWave) communications have been one of the promising technologies for future wireless networks that integrate a wide range of data-demanding applications. To compensate for the large channel attenuation in mmWave band and avoid high hardware cost, a lens-based beamspace massive multiple-input multiple-output (MIMO) system is considered. However, the spatial-wideband effect in wideband mmWave systems makes channel estimation very challenging, especially when the receiver is equipped with a limited number of radio-frequency (RF) chains. Furthermore, the real channel data cannot be obtained before the mmWave system is used in a new environment, which makes it impossible to train a deep learning (DL)-based channel estimator using real data set beforehand. To solve the problem, we propose a model-driven unsupervised learning network, named learned denoising-based generalized expectation consistent (LDGEC) signal recovery network. By utilizing the Stein's unbiased risk estimator loss, the LDGEC network can be trained only with limited measurements corresponding to the pilot symbols, instead of the real channel data. Even if designed for unsupervised learning, the LDGEC network can be supervisingly trained with the real channel via the denoiser-by-denoiser way. The numerical results demonstrate that the LDGEC-based channel estimator significantly outperforms state-of-the-art compressive sensing-based algorithms when the receiver is equipped with a small number of RF chains and low-resolution ADCs. © 2002-2012 IEEE.

关键词： Channel estimation

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Resilient Operation of DC Standalone Microgrids: Experimental Validation of Hybrid RNN-PI Control for Pulse Load Management

Resilient Operation of DC Standalone Microgrids: Experimenta...

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IEEE Green Technologies Conference (IEEE-Green)

作者： Ahmed Aghmadi Osama A. Mohammed Department of Electrical and Computer Engineering Energy Systems Research Laboratory Florida International University Miami FL USA

ISBN: (数字)9798331520182

ISBN: (纸本)9798331520199

Effective energy storage system (ESS) management is critical for enhancing the performance of standalone DC microgrids, particularly when integrating renewable energy sources such as photovoltaic (PV) or wind systems. This research describes a new hybrid control technique to improve DC microgrid operations' efficiency and resiliency, especially when handling critical loads. This research presents a hybrid closed-loop control technique that uses Recurrent Neural Networks (RNNs) and Proportional-Integral (PI) controllers to address the complex issues of dynamic load situations and transient disturbances. The RNN evaluates voltage errors to generate accurate reference currents, which the PI controllers then adjust to improve the performance of the bidirectional converter. Unlike standard PI-PI controls, our hybrid approach is particularly effective at regulating pulsed power loads (PPLs) and enhancing system response to transitory situations. The experimental results show that the RNN-PI control scheme significantly improves voltage regulation and transient responsiveness, exceeding conventional performance and resilience techniques. This approach provides a convincing solution for enhancing microgrid systems' stability and efficiency in various real-world applications.

关键词： Renewable energy sources Recurrent neural networks PI control Voltage fluctuations Microgrids Robustness Voltage control Transient analysis Standards Resilience

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Reviewing metal supported solid oxide fuel cells for efficient electricity generation with biofuels for mobility

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Journal of Energy Chemistry 2025年第4期103卷 106-153页

作者： Fábio C.Antunes João P.J.de Oliveira Ricardo S.de Abreu Thiago Dias Bruno B.N.S.Brandão Josué M.Gonçalves Josimar Ribeiro Julian Hunt Hudson Zanin Gustavo Doubek School of Electrical and Computer Engineering University of CampinasCampinas 13083-852Brazil School of Food Engineering University of CampinasCampinas 13083-852Brazil School of Chemical Engineering University of CampinasCampinas 13083-852Brazil Mackenzie Institute for Research in Graphene and Nanotechnologies(MackGraphe) Mackenzie Presbyterian InstituteSão Paulo 01302-907Brazil Electrochemistry Research and Development Laboratory(LPDE) Department of ChemistryCenter of Exact SciencesFederal University of Espírito SantoCampus GoiabeirasVitória 29075-910Brazil Biological and Environmental Science and Engineering Division King Abdullah University of Science and TechnologyThuwal 23955-6900Saudi Arabia

Metal-Supported Solid Oxide Fuel Cells(MS-SOFCs)hold significant potential for driving the energy *** electrochemical devices represent the most advanced generation of Solid Oxide Fuel Cell(SOFCs)and can pave the way for mass production and wider adoption than Proton Exchange Membrane Fuel Cells(PEMFCs)due to their fuel flexibility,higher power density and the absence of noble metals in the fabrication *** review examines the state-of-the-art of SOFCs and MS-SOFCs,presenting perspectives and research directions for these key technological devices,highlighting novel materials,techniques,architectures,devices,and degradation mechanisms to address current challenges and future *** such as infiltration/impregnation,ex-solution catalyst synthesis,and the use of a pre-catalytic reformer layer are discussed as their impact on efficiency and prolonged *** concepts are also described and connected with well-dispersed nano particles,hindrance of coarsening,and an increased number of Triple Phase Boundaries(TPBs).This review also describes the synergistic use of reformers with MS-SOFCs to compose solutions in energy generation from readily available ***,the End-of-Life(EoL),recycling,and life-cycle assessments(LCAs)of the Fuel Cell Hybrid Electric Vehicles(FCHEVs)were *** comparing Fuel Cell Electric Vehicles(FCEVs)equipped with(PEMFCs)and FCHEVs equipped with MS-SOFCs,both powered with hydrogen(H_(2))generated by different routes were *** review aims to provide valuable insights into these key technological devices,emphasizing the importance of robust research and development to enhance performance and lifespan while reducing costs and environmental impact.

关键词： Reform Metal-supported solid oxide fuel cell Powertrain systems Fuel cell Hybrid electric vehicle Biofuel

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