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European Conference on Solid-State Circuits (ESSCIRC)

作者： Guglielmo De Filippi Lorenzo Piotto Andrea Mazzanti Department of Electrical Computer and Biomedical Engineering University of Pavia Italy

ISBN: (数字)9798350388138

ISBN: (纸本)9798350388145

Emerging applications in the Sub-THz bands need ultra-wideband amplifiers, able to cover the wide available spectrum portions with a single component. Techniques such as distributed amplifiers or stagger-tuning are commonly adopted, at the cost of power efficiency, linearity and noise figure degradation. This paper proposes a design flow for ultra-wideband matching networks with a sixth-order frequency response. The networks fit well into the layout, absorbing parasitics and embedding the interconnections for signal propagation, biasing and supply of the active stages. The networks are exploited in the design of a 3-stage D-band low-noise amplifier in a SiGe BiCMOS technology. Experiments demonstrate 105- to- $175 \mathrm{GHz}-3 \mathrm{~dB}$ bandwidth with 23 dB gain. The fractional bandwidth, in excess of 50%, is among the highest reported in similar frequency bands. Simultaneously, a very low noise figure, ranging from 5 dB to 6.5 dB, confirms the validity of the proposed approach to enhance the performance of mm-Wave wideband amplifiers.

关键词： Noise figure Low-noise amplifiers Broadband amplifiers Linearity BiCMOS integrated circuits Transformers Wideband Tuning Ultra wideband technology Silicon germanium

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Total Labelings of Graphs with Prescribed Weights

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Journal of Combinatorial Mathematics and Combinatorial Computing 2024年 120卷 367-376页

作者： Bača, Martin Miller, Mirka Phanalasy, Oudone Ryan, Joe Semaničová-Feňovčíková, Andrea Sillasen, Anita A. Department of Applied Mathematics and Informatics Technical University Košice Slovakia School of Mathematical and Physical Sciences The University of Newcastle Australia School of Electrical Engineering and Computer Science The University of Newcastle Australia Department of Mathematics University of West Bohemia Pilsen Czech Republic Department of Informatics King's College London United Kingdom Department of Mathematics National University of Laos Vientiane Laos Department of Mathematical Sciences Aalborg University Aalborg Denmark

The total labeling of a graph G = (V, E) is a bijection from the union of the vertex set and the edge set of G to the set {1, 2, . . . , |V(G)| + |E(G)|}. The edge-weight of an edge under a total labeling is the sum of the label of the edge and the labels of the end vertices of that edge. The vertexweight of a vertex under a total labeling is the sum of the label of the vertex and the labels of all the edges incident with that vertex. A total labeling is called edge-magic or vertex-magic when all the edge-weights or all the vertex-weights are the same, respectively. When all the edge-weights or all the vertex-weights are different then a total labeling is called edge-antimagic or vertex-antimagic total, respectively. In this paper we deal with the problem of finding a total labeling of some classes of graphs that is simultaneously vertex-magic and edge-antimagic or simultaneously vertex-antimagic and edge-magic, respectively. We show several results for stars, paths and cycles. © 2024 Charles Babbage Research Centre. All rights reserved.

关键词： Edge-antimagic total labeling Edge-magic total labeling Vertex-antimagic total labeling Vertex-magic total labeling

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A Biasing Scheme for the Gain Compression Point Optimization of HBT Cascode D-Band LNAs

A Biasing Scheme for the Gain Compression Point Optimization...

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BiCMOS and Compound Semiconductor Integrated Circuits and Technology Symposium (BCICTS)

作者： Lorenzo Serra Guglielmo De Filippi Lorenzo Piotto Andrea Mazzanti Department of Electrical Computer and Biomedical Engineering University of Pavia Italy

ISBN: (数字)9798331541248

ISBN: (纸本)9798331541255

Cascode amplifiers with a matching network between the common-emitter (CE) and the common-base (CB) HBTs are popular in the sub-THz band for their enhanced gain. The stage is analyzed in this paper with focus on the large-signal behavior. It is first observed that the CE-CB interstage network can push the CB out of the linear class-A regime, limiting the input power at 1 dB gain compression. It is then shown that the issue can be avoided with a suitable biasing scheme, leading to enhanced dynamic range with superior power efficiency. The concept is applied to the design of a D-band LNA in BiCMOS technology. With a quiescent power consumption of 20 mW from 2 V supply, the LNA shows 17.5 dB gain and 5.5 dB NF at 170 GHz. The output-referred 1dB compression point is 4.2dBm with 9% power efficiency at 175 GHz. Compared to previously reported LNAs in the same band, measured results demonstrate a remarkable dynamic range improvement with the the highest power efficiency.

关键词： Integrated circuits Semiconductor device measurement Power measurement Power demand Limiting Dynamic range BiCMOS integrated circuits Noise measurement Gain Optimization

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Prospector Heads: Generalized Feature Attribution for Large Models & Data 41

Prospector Heads: Generalized Feature Attribution for Large ...

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41st International Conference on Machine Learning, ICML 2024

作者： Machiraju, Gautam Derry, Alexander Desai, Arjun Guha, Neel Karimi, Amir-Hossein Zou, James Altman, Russ B. Ré, Christopher Mallick, Parag Department of Biomedical Data Science Stanford University United States Cartesia AI United States Department of Computer Science Stanford University United States Department of Electrical & Computer Engineering University of Waterloo Canada Department of Radiology Stanford University United States

Feature attribution, the ability to localize regions of the input data that are relevant for classification, is an important capability for ML models in scientific and biomedical domains. Current methods for feature attribution, which rely on "explaining" the predictions of end-to-end classifiers, suffer from imprecise feature localization and are inadequate for use with small sample sizes and high-dimensional datasets due to computational challenges. We introduce prospector heads, an efficient and interpretable alternative to explanation-based attribution methods that can be applied to any encoder and any data modality. Prospector heads generalize across modalities through experiments on sequences (text), images (pathology), and graphs (protein structures), outperforming baseline attribution methods by up to 26.3 points in mean localization AUPRC. We also demonstrate how prospector heads enable improved interpretation and discovery of class-specific patterns in input data. Through their high performance, flexibility, and generalizability, prospectors provide a framework for improving trust and transparency for ML models in complex domains. Copyright 2024 by the author(s)

关键词： Data assimilation

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Automatic detection of autism spectrum disorder based on fMRI images using a novel convolutional neural network

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Research on biomedical engineering 2023年第2期39卷 407-413页

作者： Sabegh, Amin Majidzadeh Samadzadehaghdam, Nasser Seyedarabi, Hadi Ghadiri, Tahereh Department of Biomedical Engineering Faculty of Advanced Medical Sciences Tabriz University of Medical Sciences Tabriz Iran Faculty of Electrical and Computer Engineering University of Tabriz Tabriz Iran Department of Neuroscience and Cognition Faculty of Advanced Medical Sciences Tabriz University of Medical Sciences Tabriz Iran

Purpose: Heterogeneous mental disorders such as autism spectrum disorder (ASD) are difficult to diagnose, especially in children. The current psychiatric diagnosis process is based solely on the observation of behavioral symptoms. To make a supplementary decision system for a more accurate diagnosis, we can rely on advanced and scalable machine learning methods, namely, deep learning networks. Method: We have developed our model based on resting-state fMRI data from the ABIDE1 database, which includes 17 different imaging sites. After performing a preprocessing pipeline and registering the data onto the atlases, the average time series of brain regions are extracted and the correlation matrix is computed. Then, the most important features of this matrix are identified by using the chi-square feature selection method. A novel architecture of convolutional neural network (CNN) with two-dimensional convolutional layers is proposed to analyze and classify the data. Results: To evaluate the model, three sets of experiments were designed based on different data sets and atlases. Using this method, the highest accuracy obtained in the experiments was 73.53%, which was higher than previous works on classifying ASD from typical controls. Conclusion: This work presented a novel CNN-based model that automatically classifies ASD from healthy controls, showing good classification performance. Most of the previous works done on this database have focused on a limited number of sites. But in this research, the data acquired by all the sites have been used to increase the generalizability of the proposed model. © 2023, The Author(s), under exclusive licence to The Brazilian Society of biomedical engineering.

关键词： Magnetic resonance imaging

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Regenerative Braking Capabilities in E-Bike Vehicles: Comparison Between two Drive Architectures

Regenerative Braking Capabilities in E-Bike Vehicles: Compar...

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2024 IEEE International Conference on electrical Systems for Aircraft, Railway, Ship Propulsion and Road Vehicles and International Transportation Electrification Conference, ESARS-ITEC 2024

作者： Minervini, Marcello Giangrande, Paolo Corti, Fabio Malighetti, Paolo Mantione, Lorenzo University of Bergamo Department of Engineering and Applied Sciences Dalmine Italy Dinfo Università di Firenze Firenze Italy University of Bergamo Department of Management Information and Production Engineering Dalmine Italy University of Pavia Department of Electrical Computer and Biomedical Engineering Pavia Italy

ISBN: (纸本)9798350373905

A comparative study between two regenerative braking strategies implemented on a 100 kg (bike + user) overall mass e-bike system is presented. The simulation models are built in MATLAB Simulink® environment and a commercial in-wheel direct-drive brushless DC (BLDC) motor is assumed as benchmark electrical machine. In the paper, a brief literature review about regenerative braking is firstly presented. Secondly a simulation comparison between two drive schemes is reported. The first scheme is composed by a buck converter and an inverter with six-step commutation. The second scheme, however, doesn't have the buck converter and uses two different Pulse Width Modulation techniques to control the inverter for motoring function and electric braking function. The aim of the work is to study the possibilities of the implementation and the advantages of this kind of brake, useful for extending the autonomy range of a LEV. © 2024 IEEE.

关键词： MATLAB

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Quaternion double random phase encoding for privacy-preserving cancelable biometrics

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Multimedia Tools and Applications 2024年第37期83卷 85065-85078页

作者： Nasr, Mahmoud Piórkowski, Adam Abd El-Samie, Fathi E. Department of Biocybernetics and Biomedical Engineering AGH University of Krakow Krakow Poland Faculty of Engineering and Technology Future University in Egypt Cairo Egypt Computer Vision Sano Centre for Computational Medicine Kraków Poland Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Manoufia University Menouf32952 Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

Biometrics has become a fundamental aspect in the constantly-changing field of security solutions. Nevertheless, the ongoing risk of hacking and the possibility of biometric data being compromised in security breaches emphasize the urgent need for inventive and reliable biometric authentication methods. Introducing cancelable biometrics is an advanced approach to enhance the security of biometric templates. Our research paper presents a unique variation of this approach that depends on the powerful Double Random Phase Encoding (DRPE) algorithm. By incorporating an auxiliary input biometric template and using quaternion mathematics, we get an exceptional level of performance that surpasses previous performance standards. The cancelable biometric recognition system we present demonstrates exceptional performance in simulation experiments, demonstrating its ability to remain robust even in the presence of noise. More precisely, the proposed cancelable face recognition system attains a notable area under the Receiver Operating Characteristic (ROC) curve of 0.994 and an exceptionally-low Equal Error Rate (EER) of 0.00174. The efficiency of our solution is amazing, with an average time of 0.056263 seconds for each generated secure template. This demonstrates both speed and efficacy in addressing current security concerns. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Biometrics

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IT-Security Risk Based Approach for Secure Operation of Distributed Data Platforms in Supply Chains

IT-Security Risk Based Approach for Secure Operation of Dist...

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2024 IEEE International Conference on Industrial engineering and engineering Management, IEEM 2024

作者： Voß, Marvin Kallisch, Jonas Runge, Maxim Theus, Tobias Niemann, Karl-Heinz Wunck, Christoph Faculty I - Electrical Engineering and Information Technology University of Applied Sciences and Arts Hannover Germany Department of Engineering Section Electrical Engineering and Computer Science University of Applied Sciences Leer Emden Germany Faculty of Mathematics Informatics and Statistics Ludwig Maximilian University Munich Germany

ISBN: (纸本)9798350386097

This paper presents the development of a secure data platform designed to enhance operational efficiency and to facilitate cross-company collaboration within the manufacturing supply chain. The platform is designed to ease secure information exchange while maintaining the sovereignty of each participant, leveraging standardized security features and advanced technologies such as federated learning. Security measures are based on a comprehensive risk analysis, which methodically identifies, assesses, and mitigates potential threats. Moreover, federated learning models that are not transparent are utilized. This allows data owners to maintain control over sensitive information within the consortium. The described approach markedly enhances both security and operational collaboration across the industry, representing a crucial stride towards more integrated and efficient supply chain management in manufacturing. © 2024 IEEE.

关键词： Risk analysis

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TCIP: Transformed Colour Intensity Profiles analysis for fault detection in power line insulators

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Multimedia Tools and Applications 2025年第8期84卷 4503-4534页

作者： Tomaszewski, Michal Gasz, Rafal Kasana, Singara Singh Osuchowski, Jakub Singh, Simranjit Zator, Slawomir Department of Computer Science Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Prószkowska 76 Opole45-758 Poland Department of Computer Science and Information Technology Central University of Haryana Haryana Mahendergarh123031 India Department of Information Technology Dr B. R. Ambedkar National Institute of Technology Punjab Jalandhar India Department of Safety Engineering and Technical Systems Faculty of Production Engineering and Logistics Opole University of Technology Prószkowska 76 Opole45-758 Poland

In response to the escalating demand for electricity, the aging process and inherent failures in power lines have become unavoidable challenges in their operational integrity. This research addresses the imperative need for a robust method to detect damage in power insulator disc images, introducing a novel feature extraction technique grounded in color intensity profile transformation and ensemble learning. For the purposes of the research, a specific dataset was developed based on publicly available images of power insulators. The collection consists of 9232 images of insulator discs which included 2184 images of damaged discs. The discernible damages include breakages and burnouts. Two distinct analysis variants were employed. In the first variant (V1), two classification groups were selected: disc with damages and disc without damages. In the second variant (V2), three classification groups were selected: discs without damage, broken discs, and burnout discs. The described research was divided into two successive stages. In the first of them (S1), the transformed color intensity profiles for the prepared data set were built and various machine learning models for their classification were trained and evaluated. In the next stage (S2), previously developed, highest efficient machine learning models, were used to make the detection of various damaged types of overhead line insulator discs. For the first stage of research high-performance results and a high value of the F1 score parameters were obtained (F1 score = 0.999 for the first variant (S1V1) and F1 score = 0.992 for the second variant (S1V2). In the second stage of research and the first variant (S2V1), the highest result of the F1 score was 0.932 and for the second variant (S2V2) F1 score was 0.930. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Feature extraction

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Fractional Brownian motion with fluctuating diffusivities

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Physical Review E 2024年第1期110卷 014105-014105页

作者： Adrian Pacheco-Pozo Diego Krapf Department of Electrical and Computer Engineering and School of Biomedical Engineering <a href="https://***/03k1gpj17">Colorado State University</a> Fort Collins Colorado 80523 USA.

Despite the success of fractional Brownian motion (fBm) in modeling systems that exhibit anomalous diffusion due to temporal correlations, recent experimental and theoretical studies highlight the necessity for a more comprehensive approach of a generalization that incorporates heterogeneities in either the tracers or the environment. This work presents a modification of Lévy's representation of fBm for the case in which the generalized diffusion coefficient is a stochastic process. We derive analytical expressions for the autocovariance function and both ensemble- and time-averaged mean squared displacements. Further, we validate the efficacy of the developed framework in two-state systems, comparing analytical asymptotic expressions with numerical simulations.

关键词： Anomalous diffusion Fractional Brownian motion Disordered systems Statistical methods

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