检索结果-内蒙古大学图书馆

Hospital plastic waste valorization through microwave-assisted Pyrolysis: Experimental and modeling studies via machine learning

引用

Journal of Cleaner Production 2025年 514卷

作者： Potnuri, Ramesh Sankar Rao, Chinta Surya, Dadi Venkata Kumar, Abhishankar Control Systems & Machine Learning Research Laboratory Department of Chemical Engineering National Institute of Technology Karnataka Surathkal 575025 India Department of Chemical Engineering Pandit Deendayal Energy University Gandhinagar382007 India MPM Infosoft Pvt. Ltd. IIT Madras Research Park Chennai600113 India

The COVID-19 pandemic generated a global upsurge in hospital plastic waste (HPW) as a consequence of the widespread utilization of personal protective equipment (PPE) composed of diverse polymer materials. The constant demand for PPE worldwide led to the accumulation of substantial volumes of high-polymer-based plastic waste. To tackle this challenge, researchers delved into the conversion of HPW into valuable chemicals through a process known as microwave-assisted pyrolysis (MAP). This method entails the transformation of HPW into high-quality char and liquid oil, which can serve as a source of fuel. In this study, our primary focus was to understand how the ratio of HPW (hospital plastic waste) to susceptor weight influenced the yields and characteristics of the resulting products in the context of the MAP process. To facilitate the experimental setup, a Central Composite Design (CCD) was employed. The impact of varying HPW weights and susceptor quantities on the production of value-added products was investigated. The analysis of condensed organic vapor decomposition revealed an increase in liquid yields (73.6 wt %, 76.6 wt %, 80.7 wt %) as the graphite content increased at a constant 30 g HPW. Conversely, gas yield decreased with higher susceptor and HPW quantity. Keeping the graphite constant at 4g, the gas yield declined (32.5 wt %, 30.7 wt %, and 24.7 wt %) as HPW increased. Additionally, gas yield exhibited a drop (32.5 wt % to 18.1 wt %) with an increase in both graphite and HPW. Furthermore, the residual yield decreased (from 1.7 wt % to 1.2 wt %) with a 30 g increase in HPW. In-depth analysis incorporated machine learning techniques to understand the behavior of response variables about susceptor and HPW quantities. The optimization of the MAP process for HPW encompassed various supplementary operational parameters, including susceptor thermal energy, average heating rate, microwave energy, specific microwave power, and product yields. Moreover, the resid

关键词： Plastic parts

来源：评论

学校读者我要写书评

暂无评论

State Derivative Normalization for Continuous-Time Deep Neural Networks

引用

IFAC-PapersOnLine 2024年第15期58卷 253-258页

作者： Jonas Weigand Gerben I. Beintema Jonas Ulmen Daniel Görges Roland Tóth Maarten Schoukens Martin Ruskowski Chair of Machine Tools and Control Systems RPTU Kaiserslautern and the German Research Center for Artificial Intelligence Kaiserslautern Germany Control Systems (CS) Group at the Department of Electrical Engineering Eindhoven University of Technology Netherlands. R. Tóth is also affiliated to the Systems and Control Laboratory at the Institute for Computer Science and Control Budapest Hungary Institute for Electromobility RPTU Kaiserslautern Germany

The importance of proper data normalization for deep neural networks is well known. However, in continuous-time state-space model estimation, it has been observed that improper normalization of either the hidden state or hidden state derivative of the model estimate, or even of the time interval can lead to numerical and optimization challenges with deep learning based methods. This results in a reduced model quality. In this contribution, we show that these three normalization tasks are inherently coupled. Due to the existence of this coupling, we propose a solution to all three normalization challenges by introducing a normalization constant at the state derivative level. We show that the appropriate choice of the normalization constant is related to the dynamics of the to-be-identified system and we derive multiple methods of obtaining an effective normalization constant. We compare and discuss all the normalization strategies on a benchmark problem based on experimental data from a cascaded tanks system and compare our results with other methods of the identification literature.

关键词： System Identification Continuous-Time Neural Ordinary Differential Equations Nonlinear State-Space

来源：评论

学校读者我要写书评

暂无评论

Bayesian Optimization for Building Social-Influence-Free Consensus

arXiv

引用

arXiv 2025年

作者： Adachi, Masaki Chau, Siu Lun Xu, Wenjie Singh, Anurag Osborne, Michael A. Muandet, Krikamol Machine Learning Research Group University of Oxford United Kingdom Toyota Motor Corporation Japan CISPA Helmholtz Center for Information Security Germany Automatic Control Laboratory EPFL Switzerland

We introduce Social Bayesian Optimization (SBO), a vote-efficient algorithm for consensus-building in collective decision-making. In contrast to single-agent scenarios, collective decision-making encompasses group dynamics that may distort agents’ preference feedback, thereby impeding their capacity to achieve a social-influence-free consensus—the most preferable decision based on the aggregated agent utilities. We demonstrate that under mild rationality assumptions, reaching social-influence-free consensus using noisy feedback alone is impossible. To address this, SBO employs a dual voting system: cheap but noisy public votes (e.g., show of hands in a meeting), and more accurate, though expensive, private votes (e.g., one-to-one interview). We model social influence using an unknown social graph and leverage the dual voting system to efficiently learn this graph. Our theoretical findings show that social graph estimation converges faster than the black-box estimation of agents’ utilities, allowing us to reduce reliance on costly private votes early in the process. This enables efficient consensus-building primarily through noisy public votes, which are debiased based on the estimated social graph to infer social-influence-free feedback. We validate the efficacy of SBO across multiple real-world applications, including thermal comfort, team building, travel negotiation, and energy trading *** Codes 62C10, 62F15 © 2025, CC BY.

关键词： Voting machines

来源：评论

学校读者我要写书评

暂无评论

Method for Finding an Investment Strategy in the Case of a Sparse Covariance Matrix

Method for Finding an Investment Strategy in the Case of a S...

引用

International Conference on Management of Large-Scale System Development (MLSD)

作者： Victor Gorelik Tatiana Zolotova Department of Simulation Systems and Operations Research Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences Moscow Russia Department of Data Analysis and Machine Learning Financial University under the Government of the Russian Federation Moscow Russia

An optimality principle is proposed for making investment decisions based on efficiency and risk assessments with a sparse covariance matrix. The method is implemented as a program with a graphical interface and demon... 详细信息

ISBN: (数字)9798350375718

ISBN: (纸本)9798350375725

关键词： Large-scale systems Sparse matrices Risk management Covariance matrices Stock markets Portfolios Investment

来源：评论

学校读者我要写书评

暂无评论

Improving generative model-based unfolding with Schrödinger bridges

引用

Physical Review D 2024年第7期109卷 076011-076011页

作者： Sascha Diefenbacher Guan-Horng Liu Vinicius Mikuni Benjamin Nachman Weili Nie Physics Division Lawrence Berkeley National Laboratory Berkeley California 94720 USA Autonomous Control and Decision Systems Laboratory Georgia Institute of Technology Atlanta Georgia 30332 USA National Energy Research Scientific Computing Center Berkeley Lab Berkeley California 94720 USA Berkeley Institute for Data Science University of California Berkeley California 94720 USA Machine Learning Research Group NVIDIA Research

machine learning-based unfolding has enabled unbinned and high-dimensional differential cross section measurements. Two main approaches have emerged in this research area; one based on discriminative models and one based on generative models. The main advantage of discriminative models is that they learn a small correction to a starting simulation while generative models scale better to regions of phase space with little data. We propose to use Schrödinger bridges and diffusion models to create sbunfold, an unfolding approach that combines the strengths of both discriminative and generative models. The key feature of sbunfold is that its generative model maps one set of events into another without having to go through a known probability density as is the case for normalizing flows and standard diffusion models. We show that sbunfold achieves excellent performance compared to state of the art methods on a synthetic Z+jets dataset.

关键词： machine learning Particle detectors Probability theory

来源：评论

学校读者我要写书评

暂无评论

Information Security control Engineering for an Industrial Company with “1C” Software

Information Security Control Engineering for an Industrial C...

引用

Electrical, Computer and Energy Technologies (ICECET), International Conference on

作者： Alexey Yu. Zalozhnev Dmitry V. Chistov Active Systems Laboratory V.A. Trapeznikov Institute of Control Sciences Russian Academy of Sciences Moscow Russia Department of Data Analysis and Machine Learning Financial University Moscow Russia

The issues related to information security control engineering for an industrial company with “1C” software are considered in this paper. The article discusses the types of threats to the company's information resources, including collective knowledge stored on electronic media. The paper contains standards and other documents governing the development and operation of an industrial company's information security. A brief description of the 1C software platform and 1C ERP is given. To prevent unauthorized access to the IT infrastructure and misappropriation of information important to the client, a set of needed organizational and technical measures with the use of 1C software products is considered. Some practical conclusions are also given.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Effect of terahertz radiation on cells and cellular structures

引用

Frontiers of Optoelectronics 2025年第1期18卷 21-51页

作者： A.P.Rytik V.V.Tuchin Institute of Physics Saratov State UniversitySaratov 410012Russia Science Medical Center Saratov State UniversitySaratov 410012Russia Laboratory of Laser Molecular Imaging and Machine Learning Tomsk State UniversityTomsk 634050Russia Institute of Precision Mechanics and Control Federal Research Center"Saratov Scientific Center of the Russian Academy of Sciences"Saratov 410012Russia

The paper presents the results of modern research on the effects of electromagnetic terahertz radiation in the frequency range 0.5-100 THz at different levels of power density and exposure time on the viability of normal and cancer cells. As an accompanying tool for monitoring the effect of radiation on biological cells and tissues, spectroscopic research methods in the terahertz frequency range are described, and attention is focused on the possibility of using the spectra of interstitial water as a marker of pathological processes. The problem of the safety of terahertz radiation for the human body from the point of view of its effect on the structures and systems of biological cells is also considered.

关键词： Electromagnetic radiation Terahertz radiation Biological effects Living cell Cancer cells

来源：评论

学校读者我要写书评

暂无评论

State Derivative Normalization for Continuous-Time Deep Neural Networks

arXiv

引用

arXiv 2024年

作者： Weigand, Jonas Beintema, Gerben I. Ulmen, Jonas Görges, Daniel Tóth, Roland Schoukens, Maarten Ruskowski, Martin Chair of Machine Tools and Control Systems RPTU Kaiserslautern The German Research Center for Artificial Intelligence Kaiserslautern Germany Group The Department of Electrical Engineering Eindhoven University of Technology Netherlands The Systems and Control Laboratory The Institute for Computer Science and Control Budapest Hungary Institute for Electromobility RPTU Kaiserslautern Germany

关键词： Ordinary differential equations

来源：评论

学校读者我要写书评

暂无评论

A Preliminary Study on the Functional Coupling between Nerve and Blood Microcirculation for Applications in Rehabilitation Robots

A Preliminary Study on the Functional Coupling between Nerve...

引用

2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023

作者： Li, Qingge Dong, Yuanzhe Zhang, Yuxiang Wang, Xin Jiang, Naifu Huang, Jianping Cui, Han Tian, Lan Zheng, Yue Li, Xiangxin Wang, Lin Li, Guanglin Liang, Wenyuan Peng, Liang Fang, Peng Shenzhen Institute of Advanced Technology Cas Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen518055 China University of Chinese Academy of Sciences Shenzhen College of Advanced Technology Shenzhen518055 China National Research Center for Rehabilitation Technical Aids Beijing100176 China Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Institute of Automation Beijing100190 China

ISBN: (纸本)9798350325706

Rehabilitation robots play an important role in the motor function rehabilitation for stroke survivors with hemiplegia. However, the rehabilitation effect of current robots is still limited partly because a single training of motor function can be strongly affected by the decreased blood supply function of the bedridden patients. This work proposed an approach to study the coupling relationship between the motor and blood supply functions by combining the synchronously recorded EEG and cerebral blood oxygen information, where the cerebrations in different movement paradigms were analyzed from an aspect of "functional coupling". The results show that the information of oxyhemoglobin concentration change (ΔHbO) can effectively indicate the cortex activation, and a stronger blood supply is needed in cortexes to perform body movements. The correlations within motor cortexes are significantly stronger than the ones between motor and prefrontal cortexes, and a higher resistance level of extremity training will cause stronger correlations. Calculation of transfer entropy (TE) shows that there exists a bidirectional information transmission between the electrophysiological and blood supply signals, and more information is transmitted always in the direction from ΔHbO to EEG than in the opposite direction. The information transmission or the coupling relationship can be significantly enhanced by extremity movements, and large TE values are achieved in the Theta, Beta and Gamma frequency bands of EEG that correspond to motor functions. This work has demonstrated the functional coupling between nerve and blood microcirculation, which would provide a technical guidance to improve the rehabilitation effect for current robot systems and have great application potentials. © 2023 IEEE.

关键词：

来源：评论

学校读者我要写书评

暂无评论

ActMAD: Activation Matching to Align Distributions for Test-Time-Training

ActMAD: Activation Matching to Align Distributions for Test-...

引用

Conference on Computer Vision and Pattern Recognition (CVPR)

作者： M. Jehanzeb Mirza Pol Jané Soneira Wei Lin Mateusz Kozinski Horst Possegger Horst Bischof Institute for Computer Graphics and Vision TU Graz Austria Christian Doppler Laboratory for Embedded Machine Learning Institute of Control Systems KIT Germany Christian Doppler Laboratory for Semantic 3D Computer Vision

Test-Time-Training (TTT) is an approach to cope with out-of-distribution (OOD) data by adapting a trained model to distribution shifts occurring at test-time. We propose to perform this adaptation via Activation Matching (ActMAD): We analyze activations of the model and align activation statistics of the OOD test data to those of the training data. In contrast to existing methods, which model the distribution of entire channels in the ultimate layer of the feature extractor, we model the distribution of each feature in multiple layers across the network. This results in a more fine-grained supervision and makes ActMAD attain state of the art performance on CIFAR-100C and Imagenet-C. ActMAD is also architecture-and task-agnostic, which lets us go beyond image classification, and score 15.4% improvement over previous approaches when evaluating a KITTI-trained object detector on KITTI-Fog. Our experiments highlight that ActMAD can be applied to online adaptation in realistic scenarios, requiring little data to attain its full performance.

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：