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Input-Output-Improved Reservoir Computing Based on Duffing Resonator Processing Dynamic Temperature Compensation for MEMS Resonant Accelerometer

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MICROMACHINES 2023年第1期14卷 161-161页

作者： Guo, Xiaowei Yang, Wuhao Zheng, Tianyi Sun, Jie Xiong, Xingyin Wang, Zheng Zou, Xudong Chinese Acad Sci Aerosp Informat Res Inst State Key Lab Transducer Technol Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Elect Elect & Commun Engn Beijing 100049 Peoples R China

An MEMS resonant accelerometer is a temperature-sensitive device because temperature change affects the intrinsic resonant frequency of the inner silicon beam. Most classic temperature compensation methods, such as algorithm modeling and structure design, have large errors under rapid temperature changing due to the hysteresis of the temperature response of the accelerometer. To address this issue, we propose a novel reservoir computing (RC) structure based on a nonlinear silicon resonator, which is specifically improved for predicting dynamic information that is referred to as the input-output-improved reservoir computing (IOI-RC) algorithm. It combines the polynomial fitting with the RC on the input data mapping ensuring that the system always resides in the rich nonlinear state. Meanwhile, the output layer is also optimized by vector concatenation operation for higher memory capacity. Therefore, the new system has better performance in dynamic temperature compensation. In addition, the method is real-time, with easy hardware implementation that can be integrated with MEMS sensors. The experiment's result showed a 93% improvement in IOI-RC compared to raw data in a temperature range of -20-60 degrees C. The study confirmed the feasibility of RC in realizing dynamic temperature compensation precisely, which provides a potential real-time online temperature compensation method and a sensor system with edge computing.

关键词： reservoir computing nonlinear MEMS resonator algorithm optimization dynamic temperature compensation MEMS resonant accelerometer

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A closed-form solution for evaluating the Findley critical plane factor

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EUROPEAN JOURNAL OF MECHANICS A-SOLIDS 2024年 105卷

作者： Chiocca, A. Sgamma, M. Frendo, F. Univ Pisa Dept Civil & Ind Engn Pisa Italy

The fatigue assessment of structural components is a significant topic investigated both in the academia and industry. Despite the significant progress in comprehension over the past few decades, fatigue damage remains a significant challenge, often leading to unexpected component failures. One commonly used approach for fatigue assessment is the critical plane analysis, which aids in identifying the critical location and early crack propagation direction in a component. However, the conventional method for calculating critical plane factors is computationally demanding and is typically utilized only when the critical regions of the component are already known. In situations where the critical areas are difficult to be identified due to complex geometry, loads, or constraints, a more efficient method is required for evaluating critical plane factors. This research paper introduces an analytical algorithm to efficiently evaluates the widely used Findley critical plane factor. The algorithm operates within the framework of linear-elastic material behavior and proportional loading conditions, relying on tensor invariants and coordinate transformation laws. The algorithm has been tested on different component geometries, including a box-welded joint and a tubular specimen, subjected to proportional loading conditions such as tension, torsion, and a combination of them. The analytical method allowed a significant reduction in computation time while providing the exact solution of critical plane factor and critical plane orientations.

关键词： Critical plane Findley Material fatigue Computational efficiency algorithm optimization

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Research on image classification based on residual group multi-scale enhanced attention network

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COMPUTERS & ELECTRICAL ENGINEERING 2024年第PartA期118卷

作者： Wang, Chunzhi Deng, Xizhi Sun, Yun Yan, Lingyu Hubei Univ Technol Sch Comp Sci Wuhan Peoples R China

To address the challenges associated with insufficient feature extraction and gradient degradation encountered when dealing with deepening network structures in image classification tasks, this paper presents a ResGMEANet(Residual Group Multi-scale Enhanced Attention Network). The model introduces a multi-scale attention enhancement module. This design draws inspiration from the original model's capability to independently capture feature correlations in channels and spaces. By implementing shuffle operations and feature transformations within the group, our method expands the receptive field through the utilization of multiple convolution kernels. Additionally, we incorporate an improved tensor synthesis attention, building upon the traditional convolution attention, to derive attention feature maps after feature enhancement. Evaluation on the CIFAR-10 and CIFAR-100 datasets shows that ResGMEANet outperforms both the original backbone model and several existing mainstream methods in classification accuracy. This work aims to provide a new perspective for the future by combining residual neural networks with different attention mechanisms.

关键词： Multi -scale convolution Feature enhancement Image classification algorithm optimization

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Efficient algorithm for full-state quantum circuit simulation with DD compression while maintaining accuracy

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QUANTUM INFORMATION PROCESSING 2023年第11期22卷 413-413页

作者： Song, Yuhong Sha, Edwin Hsing-Mean Zhuge, Qingfeng Xu, Rui Wang, Han East China Normal Univ Sch Comp Sci & Technol Shanghai 200062 Peoples R China

With the development of noisy intermediate-scale quantum machines, quantum processors show their supremacy in specific applications. To better understand the quantum behavior and verify larger quantum bit (qubit) algorithms, simulation on classical computers becomes crucial. However, as the simulated number of qubits increases, the full-state simulation suffers exponential memory increment for state vector storing. In order to compress the state vector, some existing works reduce the memory by data encoding compressors. Nevertheless, the memory requirement remains massive. Meanwhile, others utilize compact decision diagrams (DD) to represent the state vector, which only demands linear memory size. However, the existing DD-based simulation algorithm possesses many redundant calculations that require further exploration. Besides, the traditional normalization-based nodes merging method of DD amplifies the side influences of approximate error. Therefore, to tackle the above challenges, in this paper, we first fully explore the redundancies in the recursive-based DD simulation (RecurSim) algorithm. Inspired by the regularities of the quantum circuit model, a scale-based simulation (ScaleSim) algorithm is proposed, which removes plenty of unnecessary computations. Furthermore, to eliminate the influences of approximate error, we propose a new pre-check DD building method, namely PCB, which maintains the accuracy of DD representation and produces more memory saving. Comprehensive experiments show that our method achieves up to 24124.2x acceleration and 3.2x10(7)x memory reduction than traditional DD-based methods on quantum algorithms while maintaining the representation accuracy.

关键词： Quantum circuit simulation Decision diagram algorithm optimization Error mitigation

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Establishment of an NPK nutrient monitor system in yield-graded cotton petioles under drip irrigation

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PLANT METHODS 2023年第1期19卷 97-97页

作者： Dong, Zhiqiang Liu, Yang Li, Minghua Ci, Baoxia Feng, Xiaokang Wen, Shuai Lu, Xi He, Zheng Ma, Fuyu Shihezi Univ Sch Agr Shihezi 832003 Xinjiang Peoples R China Guiyang Healthcare Vocat Univ Guiyang 550081 Guizhou Peoples R China Natl & Local Joint Engn Res Ctr Informat Managemen Shihezi 832003 Xinjiang Peoples R China

BackgroundThe determination of nutrient content in the petiole is one of the important methods for achieving cotton fertilization management. The establishment of a monitoring system for the nutrient content of cotton petioles during important growth periods under drip irrigation is of great significance for achieving precise fertilization and environmental *** total of 100 cotton fields with an annual yield of 4500-7500 kg/ha were selected among the main cotton-growing areas of Northern Xinjiang. The nitrate nitrogen (NO3--N), inorganic phosphorus (PO43--P) and inorganic potassium (K+-K) content and yield of cotton petioles were recorded. Based on a yield of 6000 kg/ha as the dividing line, a two-level and yield-graded monitoring system for NO3--N, PO43--P and K+-K in cotton petioles during important growth periods was established, and predictive yield models for NO3--N, PO43--P and K+-K in petioles during important growth periods were *** results showed found that the yields of the 100 cotton fields surveyed were normally distributed. Therefore, two yield grades were classified using 6000 kg/ha as a criterion. Under different yield-graded, the NO3--N, PO43--P and K+-K content of petiole at important growth stages was significantly positively correlated with yield. Further, the variation range of NO3--N, PO43--P and K+-K content in petioles could be used as a standard for yield-graded. In addition, a yield prediction model for the NO3--N, PO43--P and K+-K content of petioles was developed. The SSO-BP validation model performed the best (R2 = 0.96, RMSE = 0.06 t/ha, MAE = 0.05 t/ha) in the full bud stage, which was 12.9% higher than the BP validation model. However, the RMSE and MAE were decreased by 86.7% and 88.1%, *** establishment of NPK nutrition monitor system of cotton petioles under drip irrigation based on yield-graded provides an important basis for nutrition monitor of cotton petiole under drip irr

关键词： Petiole Cotton Nutritional monitor system Back propagation neural network algorithm optimization

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Study on Dense Phase Separation of Associated Gas with High Carbon Dioxide Content

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PROCESSES 2024年第12期12卷 2924页

作者： Jing, Yuxiao Zhang, Ming Wang, Qihang Zhu, Jianlu Xie, Naiya Li, Yuxing State Key Lab Offshore Oil & Gas Exploitat Beijing 100027 Peoples R China China Univ Petr East China Coll Pipeline & Civil Engn Natl Virtual Simulat Qingdao 266580 Peoples R China

With the continuous exploitation of offshore natural gas, the content of CO2 produced gradually increases. It is not economical to separate more CO2 from natural gas after transportation, and more CO2 will aggravate the corrosion of pipelines. The commonly used decarburization process is not suitable for offshore platforms, and there are problems of high energy consumption and large space occupation. Therefore, dense phase separation of associated gas with high carbon dioxide content is a better separation method. In this paper, the equation of state is optimized by comparing the experimental and CO2 system phase characteristics simulation. Based on the selected equation of state (EOS), a three-level separation model of phase equilibrium characteristics is established. The separation efficiency is simulated to complete the separation of CO2 and methane. The separation process is optimized by a genetic algorithm, and the temperature and pressure under the best separation efficiency are determined. The PR-EOS was selected as the equation with the highest calculation accuracy. Through process simulation and algorithm optimization, the best separation efficiency was 72.23%.

关键词： high carbon dioxide-associated gas equation of state dense phase separation process simulation algorithm optimization

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Official Document Identification and Data Extraction using Templates and OCR

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Procedia Computer Science 2022年 207卷 1571-1580页

作者： Cosmin Irimia Florin Harbuzariu Ionut Hazi Adrian Iftene “Alexandru Ioan Cuza” University of Iasi Faculty of Computer Science General Henri Mathias Berthelot Street No. 16 700259 Iasi Romania

Nowadays anyone possesses at least one personal document, whether it is an identity card or a driving license. In many of our daily activities, working with documents or the necessity to present them in different contexts became something normal. Given the current situation, we are all going through, having to deal with the current pandemic situation, we have adapted to some extent to new ways of communicating, working, and resolving things, in general, using Internet tools and platforms. In this context, a small part of the fight we have with the bureaucracy has been won, many of the documents that once could only be brought only in physical locations can now be scanned and sent by email or attached to a form on the website. Hoping that the pandemic has also taught us good things, we want to believe that these ways of communication will be kept in place even after this issue is over, to avoid unnecessary waste of time and congestion. The focus of this project is developing an application that can create textual information data from a simple image provided by the user that will enable the possibility of sharing digital versions of documents, making our lives so much better.

关键词： Computer vision algorithm optimization Image processing Optical Character Recognition

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A New Cochlear Prosthetic System with an Implanted DSP

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Journal of Semiconductors 2008年第9期29卷 1745-1752页

作者：麦宋平张春晁军王志华清华大学电子工程系北京100084 清华大学微电子研究所北京100084

This paper proposes a cochlear prosthetic system with an implanted digital signal processor （DSP）. This system transmits voice-band signals with a low data rate through the wireless link, free of the data-rate limitation and suitable for future development. By optimizing the speech processing algorithm and the DSP hardware design, the implanted DSP manages to execute the continuous interleaved sampling （CIS） algorithm at a clock frequency of 3MHz and a power consumption of only 1.91mW. With an analytic power-transmission efficiency of the wireless inductive link （40%）, the power overhead caused by the implanted DSP is derived as 2.87roW,which is trivial when compared with the power consumption of existing cochlear prosthetic systems （tens of milliwatts）. With the DSP implanted,this new system *** easily developed into a fully implanted cochlear prosthesis.

关键词： cochlear prosthesis low power algorithm optimization digital signal processor power-transmission efficiency

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Orthogonal Genetic algorithm for Planar Thinned Array Designs

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INTERNATIONAL JOURNAL OF ANTENNAS AND PROPAGATION 2012年第unknown期2012卷 319037.1-319037.7页

作者： Zhang, Li Jiao, Yong-Chang Chen, Bo Li, Hong Xidian Univ Natl Key Lab Antennas & Microwave Technol Xian 710071 Shaanxi Peoples R China

An orthogonal genetic algorithm (OGA) is applied to optimize the planar thinned array with a minimum peak sidelobe level. The method is a genetic algorithm based on orthogonal design. A crossover operator formed by the orthogonal array and the factor analysis is employed to enhance the genetic algorithm for optimization. In order to evaluate the performance of the OGA, 20x10-element planar thinned arrays have been designed to minimize peak sidelobe level. The optimization results by the OGA are better than the previously published results.

关键词： Genetic algorithm (GA) Orthogonal algorithm optimization Planar MGEA5 gene Orthogonal array Factor analysis side lobe level

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Application of deep learning in image recognition and diagnosis of gastric cancer

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Artificial Intelligence in Gastrointestinal Endoscopy 2021年第2期2卷 12-24页

作者： Yu Li Da Zhou Tao-Tao Liu Xi-Zhong Shen Department of Gastroenterology and Hepatology Zhongshan Hospital Affiliated to Fudan UniversityShanghai 200032China

In recent years,artificial intelligence has been extensively applied in the diagnosis of gastric cancer based on medical *** particular,using deep learning as one of the mainstream approaches in image processing has made remarkable *** this paper,we also provide a comprehensive literature survey using four electronic databases,PubMed,EMBASE,Web of Science,and *** literature search is performed until November *** article provides a summary of the existing algorithm of image recognition,reviews the available datasets used in gastric cancer diagnosis and the current trends in applications of deep learning theory in image recognition of gastric *** the theory of deep learning on endoscopic image *** further evaluate the advantages and disadvantages of the current algorithms and summarize the characteristics of the existing image datasets,then combined with the latest progress in deep learning theory,and propose suggestions on the applications of optimization *** on the existing research and application,the label,quantity,size,resolutions,and other aspects of the image dataset are also *** future developments of this field are analyzed from two perspectives including algorithm optimization and data support,aiming to improve the diagnosis accuracy and reduce the risk of misdiagnosis.

关键词： Endoscope Artificial intelligence algorithm optimization Data support

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