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A fuzzy collaborative forecasting approach based on XAI applications for cycle time range estimation

Applied Soft Computing 2024年 151卷

作者： Chen, Tin-Chih Toly Lin, Chi-Wei Lin, Yu-Cheng Department of Industrial Engineering and Management National Yang Ming Chiao Tung University 1001 University Road Hsinchu Taiwan Department of Industrial Engineering and Systems Management Feng Chia University Taiwan Department of Computer-Aided Industrial Design Overseas Chinese University 100 Chiao Kwang Rd. Taichung 40721 Taiwan

Estimating the cycle time ranges of jobs is a critical task in a factory. this study proposes a fuzzy collaborative intelligence (FCI) approach to improve the precision of cycle time range estimation. In the proposed methodology, a DNN is first built to accurately predict the cycle time of a job. A random forest (RF) is then constructed to explain the DNN. Each decision tree of the RF is fuzzified to estimate the cycle time ranges of the jobs learned by the decision tree. A fuzzy collaboration mechanism is also established between decision trees to narrow the cycle time ranges. The proposed methodology is novel because the RF is not applied to predict job cycle times but used to explain and fuzzify the DNN without solving complex nonlinear programming problems. The proposed methodology has been applied to a real case. According to the experimental results, the FCI approach improved the estimation precision by 18%. © 2023 Elsevier B.V.

关键词： Deep neural networks

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Development of a Control System for a Vibratory Lapping-Polishing Machine

Development of a Control System for a Vibratory Lapping-Poli...

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International Seminar/Workshop on Direct and Inverse Problems of Electromagnetic and Acoustic Wave Theory (DIPED)

作者： Vitaliy Korendiy Oleksandr Kachur Viktor Zakharov Department of Technical Mechanics and Engineering Graphics Department of Computer-Aided Design Lviv Polytechnic National University Lviv Ukraine Department of Technical Mechanics and Engineering Graphics "Galca" Ltd Lviv Polytechnic National University Lviv Ukraine

Vibratory equipment is widely used in various fields of mechanical, industrial, and manufacturing engineering. Particularly, such machines can be effectively implemented while carrying out finishing technological operations, e.g., glazing, polishing, and lapping of different machine parts. The present paper is focused on developing the control system for the novel design of a vibratory lapping-polishing machine driven by six solenoids. The main purpose consists in providing the circular trajectory of the working member and ensuring the machining uniformity at each point of the surface being treated. In such a case, it is proposed to actuate the solenoids with the specified time shift depending on the forced frequency needed to be provided. The duration of the signal actuating the solenoid is equal to one-sixth of the total duration of a cycle (period) of the working body oscillation. The corresponding control approach is developed and simulated in the Tinkercad application, while the control system is designed based on the Arduino hardware and software. In addition, the laboratory prototype of the vibratory lapping-polishing machine and the corresponding control system are implemented in practice. The performed laboratory studies and experimental tests substantiate the possibilities of generating the circular oscillations of the working member of the vibration-driven lapping-polishing machine. The obtained results may be useful for engineers and technologists dealing with control systems of various vibratory technological equipment based on electromagnetic and solenoid-type drives.

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Prior-Posterior Knowledge Prompting-and-Reasoning for Surgical Visual Question Localized-Answering

Prior-Posterior Knowledge Prompting-and-Reasoning for Surgic...

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International Joint Conference on Neural Networks (IJCNN)

作者： Peixi Peng Wanshu Fan Wenfei Liu Xing Yang Dongsheng Zhou School of Software Engineering Dalian University Dalian China Department of Radiology Affiliated Zhongshan Hospital of Dalian University Dalian China School of Computer Science and Technology Dalian University of Technology Dalian China National and Local Joint Engineering Laboratory of Computer Aided Design School of Software Engineering Dalian University Dalian China

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

The Surgical Visual Question Localized-Answering (VQLA) aims to locate the specific instance area while responing the associated question, which has the potential to assist junior resident doctors in understanding the surgical process and offering decision support for surgeons. Yet, this task remains a challenging job for data-driven neural networks, due to the serious reliance on surgical scene information provided by posterior knowledge. Hence, we propose a prior-posterior knowledge prompting-and-Reasoning (PPKPR) method to imitate the operational mode of a surgeon. Surgeons systematically inspect each instance within the surgical scene and its associated question, subsequently relying on their accumulated work experience to understand and answer the questions. The PPKPR comprises three modules: prior-posterior multi-domain knowledge prompter (PPMP), prior-posterior instance knowledge prompter (PPIP), and posterior knowledge Reasoner (PKR). Specifically, PPMP aligns prior-posterior multi-domain knowledge, thus prompting model to alleviate the misinterpretations of the textual question. PPIP provides the prior instance knowledge, ensuring model to focus on correct areas in the visual scene. The prompted knowledge is refined by the PKR to reasoning the final answer. Experimental results demonstrate that our method performs favorably against the state-of-the-art methods on the EndoVis-18 and EndoVis-17 datasets.

关键词： Knowledge engineering Visualization Neural networks Surgery Focusing Medical services Cognition

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ACQUISITION OF 3D MODELS OF PARTS BY REVERSE engineering PROCESS 8

ACQUISITION OF 3D MODELS OF PARTS BY REVERSE ENGINEERING PRO...

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8th International Conference on Trends in Agricultural engineering 2022, TAE 2022

作者： Hajková, Martina Drlička, Róbert Kotus, Martin Töröková, Monika Candrák, Juraj Institute of Design and Engineering Technology Faculty of Engineering SUA in Nitra Tr. A. Hlinku 2 Nitra949 76 Slovakia Department of Computer Aided Manufacturing Technologies Faculty of Manufacturing Technologies The Technical University of Kosice with a Seat in Prešov Bayerova 1 Prešov080 01 Slovakia

ISBN: (纸本)9788021332072

Currently, there are many situations in which we do not have documentation for some element, object, and we need it for various reasons. The article describes the procedure of using data from 3D scanning in a non-contact way for the reconstruction of a 3D model in modeling CAD software. The degree of approximation is determined by comparing the 3D model and the 3D scan. The accuracy of the work is checked by comparing the 3D model with the original CAD data. Obtained models can serve as data for computer-aided production, or digital imaging, for example, in virtual reality. © 2022 TAE 2022 - Proceeding of the 8th International Conference on Trends in Agricultural engineering 2022. All rights reserved.

关键词： Virtual reality

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Analysis of Some Parameters of Synthesized Anodized Aluminum Oxide Matrices 17

Analysis of Some Parameters of Synthesized Anodized Aluminum...

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17th IEEE International Conference on Advanced Trends in Radioelectronics, Telecommunications and computer engineering, TCSET 2024

作者： Bukliv, Roxoliana Adamiv, Volodymyr Bordun, Ihor Andrushchak, Nazariy Teslyuk, Ihor Andrushchak, Anatoliy Institute of Chemistry and Chemical Technologies Lviv Polytechnic National University Department of Chemistry and Technology of Inorganic Substances Lviv Ukraine O. G. Vlokh Institute of Physical Opics Ivan Franko National University of Lviv Lviv Ukraine Czestochowa University of Technology Department of Electrical Power Engineering Czestochowa Poland Lviv Polytechnic National University Department of Ecology and Sustainable Environmental Management Lviv Ukraine Lviv Politechnic National University Computer-Aided Design Systems Lviv Ukraine Lviv Polytechnic National University Department of Applied Physics and Nanomaterials Science Lviv Ukraine

ISBN: (纸本)9798331520564

Studies have been conducted on anodized aluminum oxide (AAO) nanomatrices manufactured by SmartMembranes (SM) (Germany) and InRedox (USA). An X-ray fluorescence analyzer determined the quantitative and qualitative composition of AAO matrices. It is shown that the AAO matrices have a large transparency window (250 - 2750 nm) and the dependence of the second harmonic generation (SHG) signal on the pore size. The parameters of the porous structure of the samples were estimated by isothermal processes of nitrogen adsorption/desorption at its boiling point (T = 77 K). © 2024 IEEE.

关键词： Harmonic generation

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Time-dependent global sensitivity analysis of the Doyle-Fuller-Newman model

arXiv

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arXiv 2025年

作者： Zonta, Elia Buha, Ivana Jovanovic Spinola, Michele Weißinger, Christoph Bungartz, Hans-Joachim Jossen, Andreas Technical University of Munich School of Engineering and Design Department of Energy and Process Engineering Arcisstraße 21 Munich80333 Germany Technical University of Munich School of Computation Information and Technology Department of Computer Science Boltzmannstraße 3 Garching85748 Germany Capgemini Engineering Center of Excellence Battery Frankfurter Ring 81 Munich80807 Germany

The Doyle-Fuller-Newman model is arguably the most ubiquitous electrochemical model in lithium-ion battery research. Since it is a highly nonlinear model, its input-output relations are still poorly understood. Researchers therefore often employ sensitivity analyses to elucidate relative parametric importance for certain use cases. However, some methods are ill-suited for the complexity of the model and appropriate methods often face the downside of only being applicable to scalar quantities of interest. We implement a novel framework for global sensitivity analysis of time-dependent model outputs and apply it to a drive cycle simulation. We conduct a full and a subgroup sensitivity analysis to resolve lowly sensitive parameters and explore the model error when unimportant parameters are set to arbitrary values. Our findings suggest that the method identifies insensitive parameters whose variations cause only small deviations in the voltage response of the model. By providing the methodology, we hope research questions related to parametric sensitivity for time-dependent quantities of interest, such as voltage responses, can be addressed more easily and adequately in simulative battery research and beyond. © 2025, CC BY.

关键词： Sensitivity analysis

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Reducing the Complexity of Operational Domain computation in Silicon Dangling Bond Logic 23

Reducing the Complexity of Operational Domain Computation in...

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Proceedings of the 18th ACM International Symposium on Nanoscale Architectures

作者： Marcel Walter Jan Drewniok Samuel Sze Hang Ng Konrad Walus Robert Wille Chair for Design Automation Technical University of Munich Germany TUM School of Computation Information and Technology Technical University of Munich Germany Department of Electrical and Computer Engineering University of British Columbia Canada Technical University of Munich & SCCH GmbH Germany

ISBN: (纸本)9798400703256

Silicon Dangling Bonds (SiDBs) constitute a beyond-CMOS computational nanotechnology platform that enables higher integration density and lower power consumption than contemporary CMOS nodes. Recent manufacturing breakthroughs in the domain sparked the interest of academia and industry alike in the race for a green computation future at the nanoscale. However, as the fabrication of SiDBs requires atomic precision, SiDB logic systems are inherently susceptible to environmental defects and material variations, which inevitably occur. The Operational Domain is a methodology to evaluate the resilience of SiDB logic against physical parameter variations. However, state-of-the-art implementations require a quadratic number of exponentially complex physical simulator calls to assess the operational domain. This paper presents two novel algorithms to obtain operational domains in an efficient fashion: one based on flood fill, and one based on contour tracing. Experimental evaluations confirm that they reduce the number of required simulator calls by 70.87% and 95.29 %, respectively. Particularly contour tracing achieves the shift from a quadratic to a linear relation, thereby reducing the complexity and paving the way for realizing reliable SiDB-based computing systems.

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Capacitor Minimization in Analog Synapses for Efficient and Compact Binarized SNNs

IEEE Transactions on Circuits and Systems for Artificial Int...

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IEEE Transactions on Circuits and Systems for Artificial Intelligence 2025年第2期2卷 114-125页

作者： Mikail Yayla Ming-Liang Wei Simon Thomann Albi Mema Chia-Lin Yang Jian-Jia Chen Hussam Amrouch Design Automation for Embedded Systems Group TU Dortmund University Dortmund Germany Lamarr Institute for Machine Learning and Artificial Intelligence Dortmund Germany Department of the Graduate Institute of Electronics Engineering National Taiwan University Taipei Taiwan Technical University of Munich (TUM) Munich Germany TUM School of Computation Information and Technology Chair of AI Processor Design Munich Institute of Robotics and Machine Intelligence Munich Germany Department of Computer Science and Information Engineering Graduate Institute of Electronics Engineering National Taiwan University Taipei Taiwan Department of Computer Science TU Dortmund University Dortmund Germany Lamarr Institute Dortmund Germany

Accelerating the immense workloads of Neural Networks (NNs) is a critical challenge, and analog computing-based approaches present a promising solution. Among these, the Integrate-and-Fire (IF) Spiking Neural Network (SNN) stands out for its potential in efficient neural computation. However, achieving high inference accuracy through precise multiply-accumulate (MAC) operations necessitates a large membrane capacitor—224 to 547 times larger than the synapse array at the 14nm technology node—resulting in prohibitive area costs. Additionally, the large capacitor size introduces higher energy consumption and longer access times. Thus, a key research challenge is maintaining accuracy while mitigating the costs associated with the large membrane capacitor. In this work, we propose a HW/SW Codesign method, called CapMin, for capacitor size minimization in analog computing IF-SNNs. CapMin minimizes the capacitor size by reducing the number of spike times needed for accurate operation of the HW, based on the absolute frequency of MAC level occurrences in the SW. To increase the operation of IF-SNNs to current variation, we propose the method CapMin-V, which trades capacitor size for protection based on the reduced capacitor size found in CapMin. In our experiments, CapMin achieves more than a 14 $\times$ reduction in capacitor size along with a 34% reduction in energy consumption over the state of the art, while CapMin-V achieves increased variation tolerance in the IF-SNN operation, requiring only a small increase in capacitor size.

关键词： Capacitors Circuits Accuracy Capacitance Micromechanical devices Costs Neurons Integrated circuit modeling Spiking neural networks Hardware

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Unlocking Past Information: Temporal Embeddings in Cooperative Bird’s Eye View Prediction

Unlocking Past Information: Temporal Embeddings in Cooperati...

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IEEE Symposium on Intelligent Vehicle

作者： Dominik Rößle Jeremias Gerner Klaus Bogenberger Daniel Cremers Stefanie Schmidtner Torsten Schön Department of Computer Science and AImotion Bavaria Technische Hochschule Ingolstadt Ingolstadt Germany Department of Electrical Engineering and AImotion Bavaria Technische Hochschule Ingolstadt Ingolstadt Germany School of Engineering and Design Technical University of Munich München Germany School of Computation Information and Technology Technical University of Munich Garching Germany

ISBN: (数字)9798350348811

ISBN: (纸本)9798350348828

Accurate and comprehensive Bird’s Eye View (BEV) semantic segmentation is essential for ensuring safe and proactive navigation in autonomous driving. Although cooperative perception has exceeded the detection capabilities of single-agent systems, prevalent camera-based algorithms in cooperative perception neglect valuable information derived from historical observations. This limitation becomes critical during sensor failures or communication issues as cooperative perception reverts to single-agent perception, leading to degraded performance and incomplete BEV segmentation maps. This paper introduces TempCoBEV, a temporal module designed to incorporate historical cues into current observations, thereby improving the quality and reliability of BEV map segmentations. We propose an importance-guided attention architecture to effectively integrate temporal information that prioritizes relevant properties for BEV map segmentation. TempCoBEV is an independent temporal module that seamlessly integrates into state-of-the-art camera-based cooperative perception models. We demonstrate through extensive experiments on the OPV2V dataset that TempCoBEV performs better than non-temporal models in predicting current and future BEV map segmentations, particularly in scenarios involving communication failures. We show the efficacy of TempCoBEV and its capability to integrate historical cues into the current BEV map, improving predictions under optimal communication conditions by up to 2% and under communication failures by up to 19%. The code is available at https://***/cvims/TempCoBEV.

关键词： Codes Accuracy Navigation Semantic segmentation Predictive models Reliability engineering Autonomous vehicles

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Machine learning-driven individualized gait rehabilitation: Classification, prediction, and mechanism design

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Journal of engineering and Science in Medical Diagnostics and Therapy 2020年第2期3卷 021105页

作者： Loya, Amol Deshpande, Shrinath Purwar, Anurag Computer-Aided Design and Innovation Lab Department of Mechanical Engineering Stony Brook University Stony BrookNY11794-2300 United States

This paper presents a machine learning-based approach toward designing individually targeted rehabilitation devices. This approach consists of a classification model for early detection of a disease, regression, and artificial neural networks (ANNs) models to predict the target rehabilitation gait for a specific individual, and finally a generative approach for the conditional synthesis of single degree-of-freedom linkage mechanisms for gait rehabilitation. design of mechanisms for human-machine interaction involves numerous subjective criteria and constraints in addition to the motion task. This is particularly important for the rehabilitation devices, where the size, complexity, weight, cost, and ease of use are critical factors. In this paper, we present an end-to-end computational approach for developing a device for individualized gait rehabilitation using machine learning techniques focusing on gait classification, prediction, and specialized device design. These models generate a distribution of linkage mechanisms, which strongly correlate to the distribution of target path variations. This way of formulating the problem results in a large variety of solutions to which subjective criteria can be applied to yield practically useful design concepts that would otherwise not be possible using traditional synthesis methods. Copyright © 2020 by ASME

关键词： Forecasting

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