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International Conference on Bioinformatics and Biomedical Engineering

作者： Li, Lian Wu, XiaoPei Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University HeFei China

ISBN: (纸本)9781424450893

Nowadays, the Human Computer Interaction (HCI) developments improve the research of EOG. In this paper, A new EOG-based HCI system for multimedia control is designed and implemented. A special headset named Mindset is used to detect the EOG pulses generated by blinking, and then transmit them wirelessly via Bluetooth to PC. Three modules are contained in the system, which are the wireless communication module, EOG recognition module and the multimedia control module, respectively. The system can be used as an assistant for the disable persons, also can be used for amusement among normal people. It is feasible to put the system into practical use due to its security and convenience. © 2011 IEEE.

关键词： Bluetooth

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Depth recovery from defocus images using total variation

Depth recovery from defocus images using total variation

引用

2010 International Conference on Computer Modeling and Simulation, ICCMS 2010

作者： Liu, Hong Jia, Yu Cheng, Hong Wei, Sui Education Ministry Key Laboratory of Intelligent Computing and Signal Processing Anhui University Hefei China

ISBN: (纸本)9780769539416

According to defocus imaging theory, the amount of blur in the defocus images varies with depth of the object in the scene. So depth in the scene can be recovered by estimating the blur with the knowledge of the lens parameters. A novel application of the total variation principle is made for the estimation of the amount of blur in the defocus images. Three main processes are included: the process of image defocusing is modeled using the model of anisotropic heat diffusion, then the depth recovery problem is translated into the minimum problem of energy functional with total variation regularization, and the gradient flow is used to seek the optimal solution. The recovery of focus image and the excess restrictions are avoided. The experiment results show that the algorithm is quite effective and depth information in edge is well retained particularly. Compared with the least square algorithm, depth recovery error with the total variation algorithm is reduced about 40%. © 2010 IEEE.

关键词： Recovery

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Inferring protein-protein interactions from sequence using sequence order information

Inferring protein-protein interactions from sequence using s...

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International Conference on Computer Science and Education

作者： Du, Xiuquan Cheng, Jiaxing Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei China

ISBN: (纸本)9781424460052

Identification of protein-protein interaction is crucial for nearly all biological process. In this paper, we introduce a new transformation of protein sequence based on sequence order information. We use 5594 interacting pairs of yeast organism from DIP core database as training data set, seven types organism as independent data set. The model with a new protein coding scheme obtains 88.927% accuracy, 88.243% sensitivity, 89.468% specificity, 77.864% MCC. The average performance on independent data set is 79.4999%. ©2010 IEEE.

关键词： Proteins

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Dynamic Multi-user Detection Scheme Based on CVA-SSAOMP Algorithm in Uplink Grant-Free NOMA 19

Dynamic Multi-user Detection Scheme Based on CVA-SSAOMP Algo...

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19th IEEE International Conference on Communication Technology, ICCT 2019

作者： Zhang, Jian Bai, Shichao Xu, Lei Zhang, Hongwei Fang, Hongyu Li, Xiaohui Anhui University Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Hefei China

ISBN: (纸本)9781728105352

In the uplink grant-free non-orthogonal multiple access (NOMA) scenario, since the active user at the sender has a structured sparsity transmission characteristic, the compressive sensing recovery algorithm is initially applied to the joint detection of the active user and the transmitted data. However, the existing compressive sensing recovery algorithms with unknown sparsity often require noise power or signal-to-noise ratio (SNR) as the priori conditions, which greatly reduces the algorithm adaptability in multi-user detection. Therefore, an algorithm based on cross validation aided structured sparsity adaptive orthogonal matching pursuit (CVA-SSAOMP) is proposed to realize multi-user detection in dynamic change communication scenario of channel state information (CSI). The proposed algorithm transforms the structured sparsity model into a block sparse model, and without the priori conditions above, the cross validation method in the field of statistics and machine learning is used to adaptively estimate the sparsity of active user through the residual update of cross validation. The simulation results show that, compared with the traditional orthogonal matching pursuit (OMP) algorithm, subspace pursuit (SP) algorithm and cross validation aided block sparsity adaptive subspace pursuit (CVA-BSASP) algorithm, the proposed algorithm can effectively improve the accurate estimation of the sparsity of active user and the performance of system bit error ratio (BER), and has the advantage of low-complexity. © 2019 IEEE.

关键词： Multiuser detection

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Design of Microstrip Type Broadband Directional Coupler

Design of Microstrip Type Broadband Directional Coupler

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2023 International Applied Computational Electromagnetics Society Symposium, ACES-China 2023

作者： Yan, Hang Wu, Xianliang Wang, Ruikang Wang, Gang Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Hefei China

ISBN: (纸本)9781733509657

A microstrip line broadband directional coupler is designed based on microstrip line theory. The bandwidth of the coupler is extended by using a cascade of multiple coupled lines. The isolation of the directional coupler is greatly improved by covering the microstrip line with a dielectric layer [1] and by loading the branching compensation capacitor to compensate for the odd-even mode phase velocity difference. Simulation results of ANSYS HFSS 2019 show that the return loss (S11) is greater than 20 dB, the insertion loss (S21) is less than 1.7 dB, the coupling degree (S31) is about -6dB(±0.8dB), the isolation degree (S41) is greater than 23.4dB, and the minimum directionality is greater than 17dB during 700 MHz-3700 MHz. The physical size of coupler is 18 mm × 60mm, which meets the design requirements of 6dB coupler. © 2023 Applied Computational Electromagnetics Society (ACES).

关键词： Directional couplers

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A novel wideband band-stop filter based on SRR DGS

A novel wideband band-stop filter based on SRR DGS

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AASRI International Conference on Applied Engineering Science, ICAES 2014

作者： Peng, M. Li, M.Q. Rong, B. Ding, Y. Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei China

ISBN: (纸本)9781138026490

In this paper, a novel design of theWideband Bandstop Filter, based on Split Ring Resonators, (SRR) is proposed. The Defect Ground Structure (DGS) is achieved by opening the SRR-shaped slot in the ground plane, and the metal cylinder is added between micro-strip line and the ground. With the above two methods, the wideband bandstop characteristics can be realized. This proposed structure is simulated by the high frequency simulation software HFSS 13.0, and the effect on the performance of a wideband Band-stop Filter by adding a metal column is studied. The design of Band-stop Filter structure with three cascaded SRR-shaped DGS units is proposed. Both the simulated and measured results show that the attenuation at the resonance frequency center reaches −55 dB, and its relative bandwidth less than −10 dB is extended to 42% ranging from 5.6 GHz to 8.6 GHz. Moreover, the insertion loss of passband is limited to 1.2 dB. © 2015 Taylor & Francis Group, London.

关键词： Notch filters

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Recognition algorithm for plant leaves based on adaptive supervised locally linear embedding

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International Journal of Agricultural and Biological Engineering 2013年第3期6卷 52-57页

作者： Yan Qing Liang Dong Zhang Dongyan Wang Xiu Key Laboratory of Intelligent Computing&Signal Processing Ministry of EducationAnhui UniversityHefei 230039China Beijing Research Center for Information Technology in Agriculture Beijing 100097China

Locally linear embedding(LLE)algorithm has a distinct deficiency in practical *** requires users to select the neighborhood parameter,k,which denotes the number of nearest neighbors.A new adaptive method is presented based on supervised LLE in this article.A similarity measure is formed by utilizing the Fisher projection distance,and then it is used as a threshold to select *** samples will produce different k adaptively according to the density of the data *** method is applied to classify plant *** experimental results show that the average classification rate of this new method is up to 92.4%,which is much better than the results from the traditional LLE and supervised LLE.

关键词： supervised locally linear embedding manifold learning Fisher projection adaptive neighbors leaf recognition Precision Agriculture

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Feature-Consistent Cyclic Domain Adversarial Network for Unsupervised Transfer Diagnosis of the Autoimmune Disease Igg4-Rd by Raman Spectroscopy

SSRN

引用

SSRN 2025年

作者： Zhang, Ziyang Chen, Cheng Qin, Wentao Wu, Xue Liu, Yang Wu, Lijun Lv, Xiaoyi Chang, Chenjie Chen, Xinya Chen, Zhiyuan Xu, Qianxi Li, Zhuoyu Ma, Mengsi Chen, Chen Xinjiang University College of Software Urumqi830046 China Xinjiang Cloud Computing Application Laboratory Xinjiang University Karamay834099 China School of Computer Science and Technology Xinjiang University Urumqi830046 China Key Laboratory of signal detection and processing Xinjiang University Urumqi830046 China Department of Rheumatology＆Immunology People's Hospital of Xinjiang Uygur Autonomous Region Xinjiang Urumqi China Xinjiang Clinical Research Center for Rheumatoid arthritis Xinjiang Urumqi China

Abstracts IgG4-related disease (IgG4-RD) is a multi-organ immune disorder characterized by systemic involvement, diverse pathogenesis, and rarity, which complicates its diagnosis. Traditional medical diagnostic models, predominantly based on supervised learning in machine learning or deep learning frameworks, struggle to address the scarcity of labeled data due to the diagnostic challenges of IgG4-RD. To overcome this limitation, this study proposes a novel framework based on Feature-Consistent Cyclic Domain Adversarial Networks (FCCDAN). The framework first trains a classification model on the source domain for diagnosing source domain diseases under supervised conditions. Subsequently, leveraging the source domain model, the encoder is guided to extract semantic features, while feature consistency loss is integrated into both the generator and discriminator to align the semantic features of the target domain with those of the source domain. Finally, the aligned features are processed through a pre-trained linear mapping to achieve unsupervised classification and diagnosis in the target domain. The proposed model utilizes common autoimmune diseases as a knowledge source, enabling unsupervised transfer diagnosis for IgG4-RD, and demonstrates generalizability through experiments on other disease datasets, achieving an average diagnostic accuracy of 90.62%. This represents improvements of 4.14%, 9.82%, and 10.51% over baseline models, respectively. FCCDAN expands the applicability of Raman spectroscopy in disease diagnosis, maintaining high performance even in label-scarce environments. The overall research workflow also establishes a robust paradigm for the application and advancement of domain adaptation techniques in this context. © 2025, The Authors. All rights reserved.

关键词： Adversarial machine learning

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Protein surface Modeling using active contour model 1

引用

5th International Conference on Geometric Modeling and processing (GMP 2008)

作者： Xiang, Junping Hu, Maolin Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education and School of Mathematics and Computational Science Anhui University China

ISBN: (数字)9783540792468

ISBN: (纸本)9783540792451

A PDE (partial differential equation) based method, 3D active contour model, is presented to model the surface of protein structure. Instead of generating a single molecular surface, we create a series of surfaces associated with the atomic energy inside the protein, which describe different resolutions of molecular surface. Our results indicate that the surfaces we generated are suitable for shape analysis and visualization. So, when the solvent-accessible surface is not enough to represent the features of protein structure, the evolution surface sequence may be an alternative choice. Besides, if the initial surface is smooth enough, the generated surfaces will preserve this property partly, because the evolution of the surfaces is controlled by the PDE.

关键词： chan-Vese method solvent-accessible surface evolution partial differential equation finite difference atomic energy

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Short-Time Variational Mode Decomposition

arXiv

引用

arXiv 2025年

作者： Jia, Hao Cao, Pengfei Liang, Tong Caiafa, Cesar F. Sun, Zhe Kushihashi, Yasuhiro Grau, Antoni Bolea, Yolanda Duan, Feng Solé-Casals, Jordi School of Medicine Nankai University Tianjin China Tianjin Key Laboratory of Interventional Brain-Computer Interface and Intelligent Rehabilitation Tianjin China Universitat Politècnica de Catalunya Barcelona Spain Mechanical Systems Engineering Nippon Institute of Technology Saitama Japan Villa Elisa Argentina Computational Bioengineering Laboratory Faculty of Health Data Science Juntendo University Tokyo Japan Data and Signal Processing Research Group University of Vic-Central University of Catalonia Vic Spain

Variational mode decomposition (VMD) and its extensions like Multivariate VMD (MVMD) decompose signals into ensembles of band-limited modes with narrow central frequencies. These methods utilize Fourier transformations to shift signals between time and frequency domains. However, since Fourier transformations span the entire time-domain signal, they are suboptimal for non-stationary time series. We introduce Short-Time Variational Mode Decomposition (STVMD), an innovative extension of the VMD algorithm that incorporates the Short-Time Fourier transform (STFT) to minimize the impact of local disturbances. STVMD segments signals into short time windows, converting these segments into the frequency domain. It then formulates a variational optimization problem to extract band-limited modes representing the windowed data. The optimization aims to minimize the sum of the bandwidths of these modes across the windowed data, extending the cost functions used in VMD and MVMD. Solutions are derived using the alternating direction method of multipliers, ensuring the extraction of modes with narrow bandwidths. STVMD is divided into dynamic and non-dynamic types, depending on whether the central frequencies vary with time. Our experiments show that non-dynamic STVMD is comparable to VMD with properly sized time windows, while dynamic STVMD better accommodates non-stationary signals, evidenced by reduced mode function errors and tracking of dynamic central frequencies. This effectiveness is validated by steady-state visual-evoked potentials in electroencephalogram signals. Copyright © 2025, The Authors. All rights reserved.

关键词： Cost functions

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