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Force and impulse multi-sensor based on flexible gate dielectric field effect transistor

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International Journal of Minerals,Metallurgy and Materials 2025年第1期32卷 214-220页

作者： Chao Tan Junling Lü Chunchi Zhang Dong Liang Lei Yang Zegao Wang College of Materials science and Engineering Sichuan UniversityChengdu 610065China The 54th Research institute of China Electronics Technology Group Corporation Shijiazhuang 050081China

Nowadays,force sensors play an important role in industrial production,electronic information,medical health,and many other ***-dimensional material-based filed effect transistor(2D-FET)sensors are competitive with nano-level size,lower power consumption,and accurate ***,few of them has the capability of impulse detection which is a path function,expressing the cumulative effect of the force on the particle over a period of *** we fabricated the flexible polymethyl methacrylate(PMMA)gate dielectric MoS_(2)-FET for force and impulse sensor *** systematically investigated the responses of the sensor to constant force and varying forces,and achieved the conversion factors of the drain current signals(I_(ds))to the detected impulse(I).The applied force was detected and recorded by I_(ds)with a low power consumption of~30 *** sensitivity of the device can reach~8000%and the 4×1 sensor array is able to detect and locate the normal force applied on ***,there was almost no performance loss for the device as left in the air for two months.

关键词： flexible gate dielectric transistor force sensor impulse sensor force sensor array

VGWO: Variant Grey Wolf Optimizer with High Accuracy and Low Time Complexity

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Computers, Materials & Continua 2023年第11期77卷 1617-1644页

作者： Junqiang Jiang Zhifang Sun Xiong Jiang Shengjie Jin Yinli Jiang Bo Fan School of information science and Engineering Hunan Institute of Science and TechnologyYueyang414006China Department of Computer and information science Linköping UniversityLinköping58183Sweden Department of Safety and quality Hunan Construction Investment GroupChangsha410004China

The grey wolf optimizer(GWO)is a swarm-based intelligence optimization algorithm by simulating the steps of searching,encircling,and attacking prey in the process of wolf *** with its advantages of simple principle and few parameters setting,GWO bears drawbacks such as low solution accuracy and slow convergence speed.A few recent advanced GWOs are proposed to try to overcome these ***,they are either difficult to apply to large-scale problems due to high time complexity or easily lead to early *** solve the abovementioned issues,a high-accuracy variable grey wolf optimizer(VGWO)with low time complexity is proposed in this *** first uses the symmetrical wolf strategy to generate an initial population of individuals to lay the foundation for the global seek of the algorithm,and then inspired by the simulated annealing algorithm and the differential evolution algorithm,a mutation operation for generating a new mutant individual is performed on three wolves which are randomly selected in the current wolf individuals while after each iteration.A vectorized Manhattan distance calculation method is specifically designed to evaluate the probability of selecting the mutant individual based on its status in the current wolf population for the purpose of dynamically balancing global search and fast convergence capability of VGWO.A series of experiments are conducted on 19 benchmark functions from CEC2014 and CEC2020 and three real-world engineering *** 19 benchmark functions,VGWO’s optimization results place first in 80%of comparisons to the state-of-art GWOs and the CEC2020 competition winner.A further evaluation based on the Friedman test,VGWO also outperforms all other algorithms statistically in terms of robustness with a better average ranking value.

关键词： Intelligence optimization algorithm grey wolf optimizer(GWO) manhattan distance symmetric coordinates

An Elevator Button Recognition Method Combining YOLOv5 and OCR

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Computers, Materials & Continua 2023年第4期75卷 117-131页

作者： Xinliang Tang Caixing Wang Jingfang Su Cecilia Taylor School of information science and Engineering Hebei University of Science and TechnologyShijiazhuang050000China Nankai-Birmingham institute of data science Intelligence BirminghamB100ABBritain

Fast recognition of elevator buttons is a key step for service robots toride elevators automatically. Although there are some studies in this field, noneof them can achieve real-time application due to problems such as recognitionspeed and algorithm complexity. Elevator button recognition is a comprehensiveproblem. Not only does it need to detect the position of multiple buttonsat the same time, but also needs to accurately identify the characters on eachbutton. The latest version 5 of you only look once algorithm (YOLOv5) hasthe fastest reasoning speed and can be used for detecting multiple objects inreal-time. The advantages ofYOLOv5 make it an ideal choice for detecting theposition of multiple buttons in an elevator, but it’s not good at specific wordrecognition. Optical character recognition (OCR) is a well-known techniquefor character recognition. This paper innovatively improved the YOLOv5network, integrated OCR technology, and applied them to the elevator buttonrecognition process. First, we changed the detection scale in the YOLOv5network and only maintained the detection scales of 40 ∗ 40 and 80 ∗ 80, thusimproving the overall object detection speed. Then, we put a modified OCRbranch after the YOLOv5 network to identify the numbers on the ***, we verified this method on different datasets and compared it withother typical methods. The results show that the average recall and precisionof this method are 81.2% and 92.4%. Compared with others, the accuracyof this method has reached a very high level, but the recognition speed hasreached 0.056 s, which is far higher than other methods.

关键词： Button recognition deep learning multi-object detection

Stability analysis of wireless network with improved fluid model

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Journal of Systems Engineering and Electronics 2015年第6期26卷 1149-1158页

作者： Zhichao Zhou Yang Xiao Dong Wang institute of information science Beijing Jiaotong University Beijing Key Laboratory of Advanced information science and Network Technology

Wireless communication is easily disturbed by unfortunate factors which drive the wireless environment unstable and complicated. Therefore, it is essential to consider these factors in stability analysis of the wireless network. However, wireless channel characteristics and packets collisions are neglected in the classical fluid model. A wireless TCP fluid model （WTFM） for stability analysis of wireless network is proposed based on cross layers, which not only makes the congestion control based on random early detection （RED） available for wireless network, but also provides a more accurate model to analyze the stability of wireless system theoretically. In the proposed model, active queue management, abnormality of wireless channels and packets collisions are taken into consideration. The comparisons between evaluating results from the WTFM and the practical performance from NS2 simulations validate the accuracy of the proposed WTFM in the perspectives of delay, dropping probability, throughput, sliding window size and queue length. A set of comparisons among the proposed WTFM, the classical fluid model and the convex optimization model are conducted. The results demonstrate that the proposed WTFM model performs better than other schemes in comprehensive aspects on capturing the characteristic of the wireless network and computing complexity.

关键词： stability analysis improved fluid model cross layers,collision wireless channel characteristic.

Image separation using wavelet-complex shearlet dictionary

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Journal of Systems Engineering and Electronics 2014年第2期25卷 314-321页

作者： Shuaiqi Liu Shaohai Hu Yang Xiao institute of information science Beijing Jiaotong University Beijing Key Laboratory of Advanced information science and Network Technology

This paper presents a new method for image separation through employing a combined dictionary consisting of wavelets and complex shearlets. Because the combined dictionary sparsely represents points and curvilinear singularities respectively, the image can be decomposed into pointlike and curvelike parts as accurate as possible. The proposed method based on the geo- metric separation theory introduced by Donoho in 2005 shows that accurate geometric separation of the morphologically distinct fea- tures of points and curves can be achieved by l1 minimization. The experimental results show that the proposed method can not only be effective but also greatly reduce the computing time.

关键词： geometric separation l1 minimization sparse approx-imation complex shearlet.

Study of heat transfer characteristics in PCFG fabrication technology using heat method

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Chinese Optics Letters 2011年第2期9卷 18-22页

作者：齐跃峰乔汉平毕卫红 institute of information science and Engineering Yanshan University

The fiber gratings fabrication technology with the heating method in a photonic crystal fiber （PCF） based on structural change is examined. The principle of photonic crystal fiber gratings （PCFGs） is analyzed in theory. The heat transfer theory and finite element method are used to examine the thermal field distribution in the fiber and the influence of the air hole structure in the cladding, and the parameters of the laser beam in the process of grating fabrication are discussed. The results show that gratings can be formed by the periodic collapse of air holes in the cladding of PCFs. Under double-point heating condition, the energy is uniformly distributed in the radial direction and is approximate to Gaussian distribution in the axial direction. With the same size of the luminous spot, as the layers and radius of the air holes increase, the laser power needed to make the air holes collapse decreases. With the same laser power, as the luminous spot radius increases, the needed heating time increases. Moreover, the relationship between the laser power needed and the air filling rate is obtained as the number of layers of the air holes changes from 1 to 7. This kind of PCFG can overcome the long-term thermal instability of conventional gratings in substance and thus has great potential applications in the related field of optical fiber sensors.

关键词： Crystal whiskers Fibers Finite element method Heating Laser theory Luminance Nonlinear optics Optical fiber fabrication Optical fibers Photonic crystals

Quantum entanglement and nonlocality properties of two-mode Gaussian squeezed states

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Chinese Physics B 2009年第2期18卷 418-425页

作者：向少华邵彬宋克慧 Department of Physics Beijing Institute of Technology Research institute of information science Huaihua University Department of Physics and Electronic information science Huaihua University

Quantum entanglement and nonlocality properties of a family of two-mode Gaussian pure states have been investigated. The results show that the entanglement of these states is determined by both the two-mode squeezing parameter and the difference of the two single-mode squeezing parameters. For the same two-mode squeezing parameter, these states show larger entanglement than the usual two-mode squeezed vacuum state. The violation of Bell inequality depends strongly on all the squeezing parameters of these states and disappears completely in the limit of large squeezing. In particular, these states can exhibit much stronger violation of local realism than two-mode squeezed vacuum state in the range of experimentally available squeezing values.

关键词： entanglement nonlocality Gaussian state

Scalable distributed video coding based on block SW-SPIHT

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Chinese Optics Letters 2007年第6期5卷 336-339页

作者：王安红赵耀朱振峰王浩 institute of information science Beijing Jiaotong University

Nowadays, distributed source coding （DSC） and distributed video coding （DVC） have been receiving more and more attention due to the distinct contributions to the easy encoding. At the same time, with more new requirements coming forth in the current network communication, the scalability of bit stream has been a new focus in the real applications. A scalable DVC scheme is presented without requiring layered coding in which the main attributions of DVC, namely the capabilities of easy encoding and robustness, are inherited remarkably and the property of scalability is also integrated simultaneously. Based on the block Slepian-Wolf set partitioning in hierarchical trees （SW-SPIHT）, the Wyner-Ziv frames are encoded to get the scalable bit stream. In addition, the binary motion searching is explored at the decoder with the help of a rate-variable ‘hash＇ from the encoder to improve the performance of the whole system. The final experimental results show that our system has higher peak signal-to-noise ratio （PSNR） than the pixel-domain DVC at the high bit rate. What is more, the scalability in signal-to-noise ratio （SNR） is also achieved satisfactorily.

关键词： Signal to noise ratio

Novel Rifle Number Recognition Based on Improved YOLO in Military Environment

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Computers, Materials & Continua 2024年第1期78卷 249-263页

作者： Hyun Kwon Sanghyun Lee Department of Artificial Intelligence and data science Korea Military AcademySeoulKorea Graduate School of information Security Korea Advanced Institute of Science and TechnologyDaejeonKorea

Deep neural networks perform well in image recognition,object recognition,pattern analysis,and speech *** military applications,deep neural networks can detect equipment and recognize *** military equipment,it is necessary to detect and recognize rifle management,which is an important piece of equipment,using deep neural *** have been no previous studies on the detection of real rifle numbers using real rifle image *** this study,we propose a method for detecting and recognizing rifle numbers when rifle image data are *** proposed method was designed to improve the recognition rate of a specific dataset using data fusion and transfer *** the proposed method,real rifle images and existing digit images are fusedas trainingdata,andthe final layer is transferredto theYolov5 *** detectionand recognition performance of rifle numbers was improved and analyzed using rifle image and numerical *** used actual rifle image data(K-2 rifle)and numeric image datasets,as an experimental *** was used as the machine learning *** results show that the proposed method maintains 84.42% accuracy,73.54% precision,81.81% recall,and 77.46% F1-score in detecting and recognizing rifle *** proposed method is effective in detecting rifle numbers.

关键词： Machine learning deep neural network rifle number recognition detection