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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Günther, Wiebke Popescu, Oana-Iuliana Rabel, Martin Ninad, Urmi Gerhardus, Andreas Runge, Jakob Institute of Data Science Jena Germany Technische Universität Berlin Institute of Computer Engineering and Microelectronics Berlin Germany Dresden Leipzig Germany Technische Universität Dresden Faculty of Computer Science Dresden Germany

Causal systems often exhibit variations of the underlying causal mechanisms between the variables of the system. Often, these changes are driven by different environments or internal states in which the system operates, and we refer to context variables as those variables that indicate this change in causal mechanisms. An example are the causal relations in soil moisture-temperature interactions and their dependence on soil moisture regimes: Dry soil triggers a dependence of soil moisture on latent heat, while environments with wet soil do not feature such a feedback, making it a context-specific property. Crucially, a regime or context variable such as soil moisture need not be exogenous and can be influenced by the dynamical system variables - precipitation can make a dry soil wet - leading to joint systems with endogenous context variables. In this work we investigate the assumptions for constraint-based causal discovery of context-specific information in systems with endogenous context variables. We show that naive approaches such as learning different regime graphs on masked data, or pooling all data, can lead to uninformative results. We propose an adaptive constraint-based discovery algorithm and give a detailed discussion on the connection to structural causal models, including sufficiency assumptions, which allow to prove the soundness of our algorithm and to interpret the results causally. Numerical experiments demonstrate the performance of the proposed method over alternative baselines, but they also unveil current limitations of our method. © 2024 Neural information processing systems foundation. All rights reserved.

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An Efficiency-Enhanced LCC-S Based Inductive Power Transfer Converter Throughout Battery Constant Current Charging Process 32

An Efficiency-Enhanced LCC-S Based Inductive Power Transfer ...

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32nd IEEE International Symposium on Industrial Electronics, ISIE 2023

作者： Luo, Yuying Iam, Io-Wa Ding, Zhaoyi Chan, Pak-Ian Lam, Chi-Seng University of Macau Institute of Microelectronics China University of Macau Faculty of Science and Technology Department of Electrical and Computer Engineering China

ISBN: (纸本)9798350399714

Constant current (CC) charging is a dominant charging process before the battery can be fully charged and the battery is considered as an equivalent resistance with a wide range variation during the process. However, a wide load range variation causes the transfer efficiency of inductive power transfer (IPT) converter to deviate from the optimum point. Therefore, transfer efficiency optimization measures are required during battery CC charging process with IPT converter. Herein, this paper proposed a suitable bivariate control method for a single-stage IPT converter based on inductor-capacitor-capacitor-series (LCC-S) compensation topology, which keeps the converter output current constant and improves transfer efficiency. The newly adopted bivariate control method includes two control variables, the conduction angle of the voltage-controlled semi-active rectifier (VCSAR) and the operating frequency of the inverter. The equivalent load of the VCSAR is adjusted by controlling the conduction angle, and at the same time, the operating frequency of the inverter is controlled to ensure constant current output. Finally, simulation results are presented to verify the effectiveness of the bivariate control method for the LCC-S compensated IPT converter. In addition, zero-voltage switching (ZVS) can be realized in both sides of the converter. © 2023 IEEE.

关键词： Zero voltage switching

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Graph-Based Multitask Transfer Learning for Fault Detection and Diagnosis of Few-Shot Analog Circuits

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IEEE Internet of Things Journal 2025年第12期12卷 21264-21279页

作者： Gao, Zhongyu Yan, Aibin Huang, Zhengfeng Cui, Jie Roh, Byeong-Hee Liu, Guangzhu Girard, Patrick Wen, Xiaoqing Anhui University School of Computer Science and Technology Hefei230601 China Hefei University of Technology School of Microelectronics Hefei230009 China Ajou University Department of Software and Computer Engineering Suwon16499 Korea Republic of University of Montpellier CNRS LIRMM Montpellier34095 France Kyushu Institute of Technology Department of Computer Science and Networks Fukuoka820-8502 Japan

Building an interpretable fault detection and diagnostic model based on few-shot circuit samples and prior information about circuit structures is of significant importance. To fill these gaps, we propose a graph-based multitask transfer learning (TL) method for fault detection and diagnosis of circuits under few-shot conditions. First, in order to model the interconnections of nodes in a circuit, the sample data is organized into a graph structure, and a semi-supervised graph-based structural feature fusion method is proposed. The proposed method can accept graph-structured data and process the data using feature fusion methods. Second, to improve the model performance under few-shot conditions, two TL mechanisms are proposed for the topological structure characteristics of analog circuits as well as circuit signal characteristics. Finally, through a parameter-shared strategy, we propose a task transfer-based fault diagnosis approach. Experimental results on three different circuits show that the proposed method has the best diagnostic accuracy compared to typical detection and diagnosis schemes. © 2014 IEEE.

关键词： Self-supervised learning

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A Secure and Cost-Effective Training Framework Atop Serverless Computing for Object Detection in Blasting

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computer Modeling in engineering & Sciences 2024年第5期139卷 2139-2154页

作者： Tianming Zhang Zebin Chen Haonan Guo Bojun Ren Quanmin Xie Mengke Tian Yong Wang Department of Computer and Science Shanghai Jiaotong UniversityShanghai200240China Aerospace System Engineering Shanghai Shanghai200240China State Key Laboratory of Precision Blasting Jianghan UniversityWuhan430056China Beijing Microelectronics Technology Institute Beijing100076China

The data analysis of blasting sites has always been the research goal of relevant *** rise of mobile blasting robots has aroused many researchers’interest in machine learning methods for target detection in the field of *** Computing can provide a variety of computing services for people without hardware foundations and rich software development experience,which has aroused people’s interest in how to use it in the field ofmachine *** this paper,we design a distributedmachine learning training application based on the AWS Lambda *** on data parallelism,the data aggregation and training synchronization in Function as a Service(FaaS)are effectively *** also encrypts the data set,effectively reducing the risk of data *** rent a cloud server and a Lambda,and then we conduct experiments to evaluate our *** results indicate the effectiveness,rapidity,and economy of distributed training on FaaS.

关键词： Serverless computing object detection blasting

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IEEE 11073 SDC for Pandemics like COVID-19: Example Implementation of an Isolation Room

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Current Directions in Biomedical engineering 2022年第2期8卷 352-355页

作者： Kasparick, Martin Schackmann, Dennis Klotz, Tobias Ritz, Fabian Golatowski, Frank Rethfeldt, Michael Neumuth, Thomas Timmermann, Dirk Rockstroh, Max Institute of Applied Microelectronics and Computer Engineering University of Rostock Richard-Wagner-Straße 31 Rostock Germany ICCAS University of Leipzig Leipzig Germany Drägerwerk AG and Co. KGaA Lübeck Germany Institute of Applied Microelectronics and Computer Engineering University of Rostock Rostock Germany

Treating patients in an intensive care unit (ICU) isolation room is full of challenges for the caregivers and the patients. While this is known for years, the COVID-19 pandemic has highlighted these challenges as if under a burning glass – intensified by a high number of patients at the same time. The risk of infection for the caregivers is very high inside the isolation room and the time spent for putting on and taking off personal protective equipment (PPE) is enormous. Thus, every treatment that can be performed from the anteroom of the isolation room at the same quality level as if being inside the isolation room is a potential building block for solving the challenges. However, data like vital signs have to be provided to the anteroom, alarms have to be transferred to the right caregiver at the right place, and controlling medical device parameters from the anteroom are prerequisites. The new IEEE 11073 Service-oriented Device Connectivity (SDC) series of standards is a key technology to realize this. Therefore, this paper presents an example implementation of IEEE 11073 SDC-based ICU isolation rooms by means of a demonstrator. Such systems can significantly reduce the amount of time the caregivers have to spend in the isolation room and reduce the number of clothing (PPE) changes while providing care at a level of a non-isolation room. As a midterm goal these are steps for the vision of a "silent/quiet ICU". © 2022 The Author(s), published by De Gruyter.

关键词： COVID-19

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A 13 × W, 94 mK Resolution, CMOS PD ΔΣ M Temperature-to-Digital Converter With Power-Gating Technique 49

A 13 × W, 94 mK Resolution, CMOS PD ΔΣ M Temperature-to-D...

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49th IEEE European Solid State Circuits Conference, ESSCIRC 2023

作者： Huang, Ying-Jie Huang, Yu-Chiao Chiu, Yu-Hao Tsai, Wen-Pin Liao, Yu-Te Institute of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan Novatek Microelectronics Hsinchu Taiwan

ISBN: (纸本)9798350304206

This paper presents a CMOS phase-domain delta-sigma modulator ( P D Δ Σ M) that digitizes temperaturedependent phase shifts resulting from driving a poly-phase filter (PPF) at a constant frequency. Closed-loop architecture with a power-gating technique is applied to improve linearity and power efficiency. The design is implemented in a 0.18 μ m CMOS process. The temperature sensor has an inaccuracy of ± 2.2°C(3σ) from -40°C to 85° C. Furthermore, the design achieves a resolution of 94 mK at 1 k S a/ s, while the chip area is 0.19 m m2. The power consumption is 13 μ W, resulting in an inaccuracy FoM of 161.1 n J%2. © 2023 IEEE.

关键词： Temperature sensors

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A Stretchable Leaky Integrate-and-Fire Neuron Enables Uncertainty Handling in Spiking Neural Networks

IEEE Electron Device Letters

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IEEE Electron Device Letters 2025年第6期46卷 999-1002页

作者： Mao, Linna Ke, Yizhen Su, Hengjie Zhang, Xinyang Sun, Biao Ma, Kaixue Li, Ting Institute of Biomedical Engineering Chinese Academy of Medical Sciences Peking Union Medical College Tianjin300192 China University of Houston Department of Electrical and Computer Engineering HoustonTX77005 United States Tianjin University School of Electrical and Information Engineering Tianjin300072 China Tianjin University School of Microelectronics Tianjin300072 China

Flexible neuromorphic computing systems have emerged as a promising candidate for next-generation edge computing systems, especially for the development of lightweight, low-power spiking neural network (SNN) systems. However, the mechanical coupling noise caused by flexible components poses challenges in uncertainty handling during the inference process in SNNs. Herein, we developed a stretchable leaky integrate-and-fire neuron device with enhanced uncertainty handling capabilities for stochastic SNN hardware implementation. These neuron devices utilize strain-induced uncertainty to model neuronal function as a conditional random variable. In addition, the SNN was incorporated in a Bayesian approximation model when the firing patterns exhibit mean stationarity over time steps. Simulations on classification and regression tasks on various datasets performed improved confidence and high generalization capability. The results demonstrate that the stretchable LIF neurons have significant potential for constructing robust and accurate SNNs for flexible neuromorphic computing. © 1980-2012 IEEE.

关键词： Edge computing

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Test Circuit Design for Accurately Characterizing Cells' Output Currents in a Read-Decoupled 8T SRAM Array for Computing-in-Memory Applications 35

Test Circuit Design for Accurately Characterizing Cells' Out...

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35th International Conference on Microelectronic Test Structure, ICMTS 2023

作者： Hong, Hao-Chiao Lin, Long-Yi Chen, Bo-Chang Institute of Electrical and Computer Engineering National Yang Ming Chiao Tung University Institute of Electrical and Control Engineering Hsinchu30010 Taiwan Novatek MicroElectronics Corp. Hsinchu Taiwan

ISBN: (纸本)9798350346534

Computing-in-memory (CIM) is a promising technique for energy-efficiently conducting the massive amount of required multiply-And-Accumulate (MAC) calculations in neural networks (NNs). The read-decoupled 8T (RD8T) SRAM cell is popular in the CIM designs because of being read disturbance free. However, local process variations may lead significant errors to the CIM results. This work proposes an accurate on-chip test circuit design for characterizing the output current of every RD8T SRAM cell in a 8-kb RD8T SRAM array fabricated in 90nm CMOS. The experimental results show the detailed and accurate spatial distribution of the RD8T cells which helps optimize the CIM circuit design. © 2023 IEEE.

关键词： Static random access storage

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Towards Human Posture Detection Basedon Differential Measurements Using Wearable Barometric Pressure Sensors

Towards Human Posture Detection Basedon Differential Measure...

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18th International Joint Conference on Biomedical engineering Systems and Technologies, BIOSTEC 2025

作者： Graumüller, Nico Gis, Constantin Geiger, Franziska Soodmand, Iman Kebbach, Maeruan Bader, Rainer Haubelt, Christian Grãtzmacher, Florian Institute of Applied Microelectronics and Computer Engineering University of Rostock Rostock18059 Germany Department of Orthopaedics Rostock University Medical Center Rostock18057 Germany

The detection of human postures is a well-studied research area that is closely related to human activity recognition. Recent advantages of MEMS-based barometric pressure sensors have made them an interesting additional sensing modality apart from IMU-based approaches. State-of-the-art barometric pressure sensors allow for measuring changes in barometric pressure corresponding to height differences in the range of centimeters. However, they are susceptible to environmental pressure changes, which can significantly influence the application. Therefore, we propose a posture detection approach based on differential height measurements from multiple body-worn barometric pressure sensors. We conducted an initial laboratory study with 13 subjects (eight males and four females), evaluating standing, sitting, and lying down postures using four body-worn barometric pressure sensors positioned at the head, hip, wrist, and ankle. Our results demonstrate that only two sensors are needed to separ ate the studied postures in the feature space. Furthermore, the differential height measurement approach can compensate for environmental pressure influences to an insignificant level w.r.t. posture separability in our setup. The efficacy of our proposed approach is further substantiated by the observed separability of sitting on a bed and a chair for each subject individually. © 2025 by SCITEPRESS– Science and Technology Publications, Lda.

关键词： Pressure sensors

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Low-Complexity Channel Estimation for RIS-Assisted ISAC System

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China Communications 2025年第4期22卷 296-308页

作者： Chen Zhen Li Jianqing Zhang Haijun Zhang Wei The Institute of Microelectronics University of MacaoMacao 999078China School of Computer Science and Engineering Macao University of Science and TechnologyMacao 999078China Beijing Engineering and Technology Research Center for Convergence Networks and Ubiquitous Services University of Science and Technology BeijingBeijing 100083China Henan Academy of Science Applied Physics Institute Co. LtdZhengzhou 450008China

Integrated sensing and communication(ISAC),assisted by reconfigurable intelligent surface(RIS)has emerged as a breakthrough technology to improve the capacity and reliability of 6G wireless ***,a significant challenge in RIS-ISAC systems is the acquisition of channel state information(CSI),largely due to co-channel interference,which hinders meeting the required reliability *** address this issue,a minimax-concave penalty(MCP)-based CSI refinement scheme is *** approach utilizes an element-grouping strategy to jointly estimate the ISAC channel and the RIS phase shift *** previous methods,our scheme exploits the inherent sparsity in RIS-assisted ISAC channels to reduce training overhead,and the near-optimal solution is derived for our studied RIS-ISAC *** effectiveness of the element-grouping strategy is validated through simulation experiments,demonstrating superior channel estimation results when compared to existing benchmarks.

关键词： channel estimation element grouping integrated sensing and communication(ISAC) RIS

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