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42nd IEEE/ACM International Conference on Computer-Aided design, ICCAD 2023

作者： Kumar, Shubham Chauhan, Yogesh Singh Amrouch, Hussam Stuttgart Germany Indian Institute of Technology Kanpur Department of Electrical Engineering India Ai Processor Design Germany Munich Institute of Robotics and Machine Intelligence Tum Germany

ISBN: (纸本)9798350315592

Monolithic three-dimensional (M3D) integration signifies a notable technological leap by providing solutions of high density and energy efficiency, particularly for ultra-efficient edge AI solutions. Among emerging technologies, ferroelectric thin-film transistors (FeTFTs) have attracted substantial interest due to their potential in neuromorphic computing and their compatibility with back-end-of-the-line (BEOL) fabrication processes. Nevertheless, the challenge of M3D integrated circuits lies in elevated temperatures resulting from limited heat dissipation across various stacked tiers, subsequently exerting adverse effects on system reliability. In this work, we explore how compute-in-memory (CIM) architectures can be realized using BEOL FeTFT to accelerate deep learning applications. We demonstrate how generated temperature impacts the reliability and ultimately degrade the inference accuracy. To achieve that, we have modified the open-source '3D+NeuroSim' framework to introduce FeTFT and then employed it to estimate the key figures of merit, such as throughput, power density, area, etc. Then, we perform a comprehensive thermal analysis for the simulated M3D architecture to explore how the DNN accuracy will be impacted due to the generated heat. We also demonstrate how FeTFT devices can be accurately modeled using TCAD simulations and how run-time variability (due to temperature effects) and design-time variability (due to process variation) impact the reliability of FeTFT transistors. © 2023 IEEE.

关键词： Thermoanalysis

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Bioactive injectable composites based on insulin-functionalized silica particles reinforced polymeric hydrogels for potential applications in bone tissue engineering

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Journal of Materials Science & Technology 2022年第10期105卷 153-163页

作者： Aleksandra Krajcer Joanna Klara Wojciech Horak Joanna Lewandowska-Łańcucka Faculty of Chemistry Jagiellonian UniversityGronostajowa 2Kraków 30-387Poland AGH University of Science and Technology Faculty of Mechanical Engineering and RoboticsDepartment of Machine Design and TechnologyAl.Mickiewicza 30Kraków 30-059Poland

Novel bioactive injectable composites based on biopolymeric hydrogels reinforced with insulin-functionalized silica particles were *** insulin(INS)was immobilized on the surface of amine-modifed silica particles employing covalent attachment by EDC/NHS chemistry and via electrostatic *** resulting formulations were examined for the morphology(SEM),chemical composition(FTIR,XPS)as well as protein *** facilitate the injectability and support the bone regeneration,developed particles were dispersed in biopolymeric sol composed of collagen,chitosan and lysinemodifed hyaluronic acid and crosslinked with *** means of rheological study,the sol-gel in situ transition of obtained systems was *** was found in vitro study that MG-63 cells cultured on the developed composites exhibit signifcantly higher alkaline phosphatase(ALP)activity,compared to the pristine ***,the biomineralization ability in the simulated body fluid(SBF)model was also *** fndings suggest that proposed herein novel hydrogel-based composites might be the promising formulation for regeneration of bone defects,especially as a less-cost effective support/alternative for BMP-2 systems.

关键词： Injectable composites Biopolymers Insulin-functionalized silica particles Bone tissue engineering

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Analysis and Characterization of Defects in FeFETs

Analysis and Characterization of Defects in FeFETs

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2023 IEEE International Test Conference, ITC 2023

作者： Thapar, Dhruv Thomann, Simon Chaudhuri, Arjun Amrouch, Hussam Chakrabarty, Krishnendu Duke University Department of Electrical and Computer Engineering North Carolina United States Ai Processor Design Germany Munich Institute of Robotics and Machine Intelligence Technical University of Munich Germany Arizona United States

ISBN: (纸本)9798350343250

Emerging devices are susceptible to manufacturing defects due to immature fabrication processes. Ferroelectric field-effect transistors, referred to as FeFETs, are promising emerging devices, but the impact of manufacturing imperfections on these devices has yet to be studied. Thus, we combine a technology CAD (TCAD) model with a fault-injection technique to represent fabrication defects in a FeFET. The TCAD model is calibrated against a fabricated metal-ferroelectric-metal capacitor and uses a multi-domain ferroelectric-layer structure. We address two classes of defects in the ferroelectric layer and map them to stuck-at-fault models referred to as neutral faults (SAP°) and stuck-at-plus and stuck-at-minus (SAP+ and SAP-) faults. We also develop a machine-learning (ML) framework to characterize these fault-injected FeFET devices. The ML framework provides a significant speedup in predicting the health of the FE layer as compared to computationally heavy TCAD simulations. Our study of defects in ferroelectric FET (FeFET), which is done for the first time, and the insights gained thereof can provide valuable feedback for the fabrication and yield learning of FeFET-based circuits. © 2023 IEEE.

关键词： Defects

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Biomechanical Test Setup for the Investigation of Forehead Suture Techniques

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Current Directions in Biomedical Engineering 2023年第1期9卷 532-535页

作者： Micheler, Carina M. Lang, Jan J. Wilhelm, Nikolas J. Schaack, Victor G. Eisenhart-Rothe, Rüdiger Von Burgkart, Rainer H. H. Bäumlisberger, Anja Wachtel, Nikolaus Department of Orthopaedics and Sports Orthopaedics University Hospital Rechts der Isar School of Medicine Technical University of Munich Munich Germany Institute for Machine Tools and Industrial Management School of Engineering and Design Technical University of Munich Garching near Munich Germany Non-destructive Testing School of Engineering and Design Technical University of Munich Munich Germany Munich Institute of Robotics and Machine Intelligence Department of Electrical and Computer Engineering Technical University of Munich Munich Germany Division of Hand Plastic and Aesthetic Surgery University Hospital LMU Munich Munich Germany

Wound healing can be delayed if the biomechanical stability of the wound closure is inadequate. Therefore, it is necessary to investigate different suturing techniques for their biomechanical stability. In this study, suturing techniques suitable for the forehead area were investigated. For this application, a special test setup was developed to simulate the curvature of the forehead and the corresponding physiological configuration. The average forehead curvature is 62.24 ± 4.11 mm in radius. To simulate this curvature, the skin specimens are subjected to tensile stress over the spherical surface using a standard uniaxial testing machine. For the evaluation, an automated evaluation tool for MATLAB was also developed. Three different suturing techniques (Straight, Lazy-S, Zigzag) were investigated and tested for their biomechanical stability. Of the three suturing techniques, the Zigzag suture proved to be the most stable with the highest stiffness of 44.23 ± 8.18 % and the highest final failure of 32.60 ± 4.95 % (relative to the control sample without incision). The study has shown that the test setup can be used to investigate different forehead suture techniques. © 2023 the author(s), published by Walter de Gruyter Berlin/Boston.

关键词： MATLAB

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Tele-rehabilitation of Upper Extremity with GARMI Robot: Concept and Preliminary Results

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IFAC-PapersOnLine 2023年第2期56卷 3546-3551页

作者： Xiao Chen Hamid Sadeghian Yanan Li Sami Haddadin Munich Institute of Robotics and Machine Intelligence Technical University of Munich 80992 Munich Germany Department of Engineering and Design University of Sussex Brighton United Kingdom

The discrepancy between the growing need for rehabilitation and the inadequate availability of facilities and skilled therapists is becoming increasingly conspicuous. To address this problem, a tele-rehabilitation system of the upper extremity with the service robot GARMI is proposed. The system utilizes optimal control and game theory, considering the patient, GARMI and possibly the therapist as the agents who share a common cost function. By adapting the roles of these agents, the proposed system can provide passive, active, and assist-as-needed rehabilitation.

关键词： Active Rehabilitation Optimal control Impedance Control

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Improved Capon Estimator for High-Resolution DOA Estimation and Its Statistical Analysis

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IEEE/CAA Journal of Automatica Sinica 2023年第8期10卷 1716-1729页

作者： Weiliang Zuo Jingmin Xin Changnong Liu Nanning Zheng Akira Sano IEEE the National Key Laboratory of Human-Machine Hybrid Augmented Intelligence the National Engineering Research Center for Visual Information and Applicationsand the Institute of Artificial Intelligence and RoboticsXi’an Jiaotong UniversityXi’an 710049China the Data Center China Construction BankBeijing 100033China the Department of System Design Engineering Keio UniversityYokohama 223-8522Japan

Despite some efforts and attempts have been made to improve the direction-of-arrival(DOA)estimation performance of the standard Capon beamformer(SCB)in array processing,rigorous statistical performance analyses of these modified Capon estimators are still *** paper studies an improved Capon estimator(ICE)for estimating the DOAs of multiple uncorrelated narrowband signals,where the higherorder inverse(sample)array covariance matrix is used in the Capon-like cost *** establishing the relationship between this nonparametric estimator and the parametric and classic subspace-based MUSIC(multiple signal classification),it is clarified that as long as the power order of the inverse covariance matrix is increased to reduce the influence of signal subspace components in the ICE,the estimation performance of the ICE becomes equivalent to that of the MUSIC regardless of the signal-to-noise ratio(SNR).Furthermore the statistical performance of the ICE is analyzed,and the large-sample mean-squared-error(MSE)expression of the estimated DOA is *** the effectiveness and the theoretical analysis of the ICE are substantiated through numerical examples,where the Cramer-Rao lower bound(CRB)is used to evaluate the validity of the derived asymptotic MSE expression.

关键词： Capon beamformer direction-of-arrival(DOA)estimation large-sample mean-squared-error(MSE) subspace-based methods uniform linear array

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Camera-LiDAR Inconsistency Analysis for Active Learning in Object Detection

Camera-LiDAR Inconsistency Analysis for Active Learning in O...

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IEEE Symposium on Intelligent Vehicle

作者： Esteban Rivera Ana Clara Serra Do Nascimento Markus Lienkamp Technical University of Munich Germany Department of Mobility Systems Engineering School of Engineering and Design Institute of Automotive Technology Munich Institute of Robotics and Machine Intelligence (MIRMI)

ISBN: (数字)9798350348811

ISBN: (纸本)9798350348828

Today, deep learning detectors for autonomous driving are delivering impressive results on public datasets and in real-world applications. However, these detectors require large amounts of data, especially labeled data, to achieve the performance needed to ensure safe driving. The process of collecting and tagging data is expensive and cumbersome. Therefore, the recent focus of the industry has been on how to achieve similar performance while limiting the amount of labeled data required to train such models. Within the cross-modal active learning paradigm, we propose and analyze new strategies to exploit the inconsistencies between camera and LiDAR detectors to improve sampling efficiency and label only the samples that promise improvements for model training. For this, we leverage the 2D projection of the bounding boxes to equalize the output quality of camera and LiDAR detections. Finally, we achieve up to 0.6% AP improvement for camera and 2% improvement for LiDAR over random sampling on the KITTI dataset using a sampling strategy based on the number of detected objects.

关键词： Training Industries Laser radar Three-dimensional displays Limiting Detectors Object detection

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A Novel Information-Theoretic Metric for Evaluating LiDAR Setups of Autonomous Vehicles

A Novel Information-Theoretic Metric for Evaluating LiDAR Se...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Philipp Hafemann Xulin Song David Brecht Technical University of Munich Germany Department of Mobility Systems Engineering School of Engineering & Design Institute of Automotive Technology and Munich Institute of Robotics and Machine Intelligence (MIRMI)

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

The sensor configuration of an autonomous vehicle (AV) is determined in the early development phase when specific perception algorithms are not yet available. Therefore, approaches based on synthetic raw data are necessary to evaluate different configurations. One sensor type used in AV is LiDAR, but developers should carefully consider the amount and placement of the sensors due to their high costs. In this contribution, we propose the Omni-Lidar Evaluation Score (OLES), a novel metric to evaluate different LiDAR configurations based on their simulated raw data. Our OLES metric combines information-theoretic quantities with coverage-based metrics, considering both the spatial coverage and the uniformity of a LiDAR point cloud distribution. We show the need for a new metric and provide details on implementing OLES using the open-source simulator CARLA. We demonstrate the effectiveness of our new metric in a simulation study and highlight its usefulness in the early phases of vehicle development. This research provides a means to evaluate the quality of LiDAR configurations and provides a basis for further optimizing sensor setups for AVs.

关键词： Measurement Point cloud compression Laser radar Costs Autonomous vehicles Cybernetics Information theory

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Estimating speaker direction on a humanoid robot with binaural acoustic signals

arXiv

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arXiv 2023年

作者： Barot, Pranav Mombaur, Katja MacDonald, Ewen N. Department of Systems Design Engineering University of Waterloo WaterlooON Canada Optimization and Biomechanics for Human-Centred Robotics Karlsruhe Germany and CERC Human-Centred Robotics and Machine Intelligence Department of Systems Design Engineering University of Waterloo Waterloo Canada

To achieve human-like behaviour during speech interactions, it is necessary for a humanoid robot to estimate the location of a human talker. Here, we present a method to optimize the parameters used for the direction of arrival (DOA) estimation, while also considering real-time applications for human-robot interaction scenarios. This method is applied to binaural sound source localization framework on a humanoid robotic head. Real data is collected and annotated for this work. Optimizations are performed via a brute force method and a Bayesian model based method, results are validated and discussed, and effects on latency for real-time use are also explored. © 2023, CC BY.

关键词： Anthropomorphic robots

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An Audio-Video Sensor Fusion Framework To Augment Humanoid Capabilities For Identifying And Interacting With Human Conversational Partners

An Audio-Video Sensor Fusion Framework To Augment Humanoid C...

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IEEE-RAS International Conference on Humanoid Robots

作者： Pranav Barot Ewen N. MacDonald Katja Mombaur Department of Systems Design Engineering University of Waterloo Canada Department of Systems Design Engineering University of Waterloo Optimization and Biomechanics for Human-Centred Robotics Karlsruhe Germany and CERC Human-Centred Robotics and Machine Intelligence Karlsruhe Institute of Technology (KIT) Institute of Anthropomatics and Robotics (IAR) Waterloo Canada

Human robot interaction often requires many sub-systems to work together in order to facilitate more natural and intelligent interactions with multiple humans. For this work, the relevant systems include audio and visual direction of arrival estimation that are used in an encompassing sensor fusion framework. The presented sub-systems are used concurrently online to allow for humanoid robots to identify active speakers in a scene, track human subjects, and identify when other subjects may require attention. We present evaluations of performance, while also implementing relevant humanlike behaviours on the REEM-C Humanoid Robot. A conducted user study delivers valuable feedback on these systems, which provide a strong foundation for improved humanoid intelligence and more innovative human-robot interaction.

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