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Marine Predators Algorithm with Deep Learning-Based Leukemia Cancer Classification on Medical Images

Computer Modeling in engineering & sciences 2024年第10期141卷 893-916页

作者： Sonali Das Saroja Kumar Rout Sujit Kumar Panda Pradyumna Kumar Mohapatra Abdulaziz S.Almazyad Muhammed Basheer Jasser Guojiang Xiong Ali Wagdy Mohamed Department of Computer Science&Engineering Gandhi Institute for TechnologyBPUTBhubaneswar752054India Department of Information Technology Vardhaman College of Engineering(Autonomous)Hyderabad501218TelanganaIndia Department of Electronic&Communication Engineering Vedang Institute of TechnologyBhubaneswar752010India Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Department of Computing and Information Systems School of Engineering and TechnologySunway UniversityJalan UniversitiBandar SunwaySelangor Darul Ehsan47500Malaysia Research Centre for Human-Machine Collaboration(HUMAC) School of Engineering and TechnologySunway UniversityJalan UniversitiBandar SunwaySelangor Darul Ehsan47500Malaysia Guizhou Key Laboratory of Intelligent Technology in Power System College of Electrical EngineeringGuizhou UniversityGuiyang550025China Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmman11931Jordan

In blood or bone marrow,leukemia is a form of cancer.A person with leukemia has an expansion of white blood cells(WBCs).It primarily affects children and rarely affects *** depends on the type of leukemia and the extent to which cancer has established throughout the *** leukemia in the initial stage is vital to providing timely patient *** image-analysis-related approaches grant safer,quicker,and less costly solutions while ignoring the difficulties of these invasive *** can be simple to generalize Computer vision(CV)-based and image-processing techniques and eradicate human *** researchers have implemented computer-aided diagnosticmethods andmachine learning(ML)for laboratory image analysis,hopefully overcoming the limitations of late leukemia detection and determining its *** study establishes a Marine Predators Algorithm with Deep Learning Leukemia Cancer Classification(MPADL-LCC)algorithm onMedical *** projectedMPADL-LCC system uses a bilateral filtering(BF)technique to pre-process medical *** MPADL-LCC system uses Faster SqueezeNet withMarine Predators Algorithm(MPA)as a hyperparameter optimizer for feature ***,the denoising autoencoder(DAE)methodology can be executed to accurately detect and classify leukemia *** hyperparameter tuning process using MPA helps enhance leukemia cancer classification *** results are compared with other recent approaches concerning various measurements and the MPADL-LCC algorithm exhibits the best results over other recent approaches.

关键词： Leukemia cancer medical imaging image classification deep learning marine predators algorithm

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Automated Parts Segmentation of Sperm via a Contrastive Learning-Based Part Matching Network

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IEEE Transactions on Automation science and engineering 2025年 22卷 15314-15325页

作者： Chen, Wenyuan Song, Haocong Shan, Guanqiao Dai, Changsheng Liu, Hang Jiang, Aojun Sun, Chen Ru, Changhai Librach, Clifford Zhang, Zhuoran Sun, Yu University of Toronto Department of Computer Science TorontoONM5S 2E4 Canada University of Toronto Department of Mechanical and Industrial Engineering TorontoONM5S 3G8 Canada Dalian University of Technology Institute of Robotics and Intelligent Systems Liaoning Dalian China Suzhou University of Science and Technology School of Electronic and Information Engineering Suzhou215009 China CReATe Fertility Centre TorontoONM5G 1N8 Canada

Sperm morphology measurement is vital for diagnosing male infertility, which involves quantification of multiple subcellular parts for each sperm. Instance-aware part segmentation networks have been introduced to address this task by automatically identifying individual sperm and segmenting their subcellular parts. However, major limitations of state-of-the-art instance-aware part segmentation networks include: 1) they are time-consuming and computational expensive due to sequential processing and multi-stage frameworks;2) they perform poorly for densely packed sperm that overlap or cross over one another. To overcome these challenges, this paper proposes 1) integrating instance identification and subcellular part segmentation within a single-stage framework to save inference time and memory usage;2) dividing a sperm target into simpler components (head and tail) to improve prediction accuracy, followed by a contrastive learning-based matching method to pair the head and tail. Experimental results on our clinically collected human sperm dataset demonstrated that the proposed network not only outperformed state-of-the-art CP-Net (by 3.5% APpvol) but also achieved realtime inference (48.0 frames per second), effectively meeting the clinical requirements for automated parts segmentation of sperm. © 2004-2012 IEEE.

关键词： Image segmentation

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Non-Rigid Point Set Registration Based on Global Prior and Local Structural Constraint 2

Non-Rigid Point Set Registration Based on Global Prior and L...

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2nd International Conference on Computer engineering and Application, ICCEA 2021

作者： Chang, Xin Fang, Shun Wu, Shiqian School of Information Science and Engineering Wuhan University of Science and Technology Institute of Robotics and Intelligent Systems Wuhan China

ISBN: (纸本)9781665426169

Coherent point drift (CPD) is a classic non-rigid point set registration algorithm. Inspired by the CPD idea, an improved CPD method is proposed in this paper. Firstly, we establish a global prior based on the graph feature to dynamically allocate Gaussian components. Secondly, a new neighborhood is defined to flexibly adjust the range of unevenly distributed points. Finally, a local structure constraint based on local neighborhood is proposed, which ensures the structure stability of the point sets. Experimental results on synthetic and real data sets show that the proposed method achieves good performance in degraded data, such as deformation, rotation, and noise. © 2021 IEEE.

关键词： Gaussian distribution

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Multi-stage Objective Function Optimized Hand-Eye Self-calibration of Robot in Autonomous Environment 1

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17th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2022

作者： Liu, Kaibo Zheng, Wangli Min, Huasong Lin, Yunhan School of Computer Science and Technology Wuhan University of Science and Technology Hubei Wuhan430065 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan University of Science and Technology Hubei Wuhan430065 China State Grid Electric Power Research Institute Jiangsu Nanjing211106 China Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology Hubei Wuhan430081 China

ISBN: (数字)9789819915491

ISBN: (纸本)9789819915484

In the application scenario of robot autonomous tasks, the robot needs to be able to complete calibration online and automatically to achieve self-maintenance, which differs from traditional robot hand-eye calibration in that the traditional robot hand-eye calibration requires a dedicated calibration board to assist offline completion. Aiming at the problem that the existing self-calibration methods cannot be optimized as a whole, which leads to low accuracy and instability of the solution, a multi-stage objective function optimization self-calibration algorithm is proposed, which describes the solution of hand-eye self-calibration as a minimization objective function problem involving multiple stages. An optimization method based on the minimization of re-projection error is designed to compensate for the results, which uses an efficient Oriented fast and rotated brief (ORB) feature extraction algorithm and introduces a scoring mechanism to retain more correct matching points in the feature matching stage. Two different types of experiments were designed to validate our method. One is a single camera dataset experiment, which shows that our method is more accurate and robust than the existing self-calibration method;the other is an application platform experiment, which verifies the feasibility and availability of our method. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Calibration

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A Client Selection Method Based on Loss Function Optimization for Federated Learning

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Computer Modeling in engineering & sciences 2023年第10期137卷 1047-1064页

作者： Yan Zeng Siyuan Teng Tian Xiang Jilin Zhang Yuankai Mu Yongjian Ren Jian Wan School of Computer Science and Technology Hangzhou Dianzi UniversityHangzhou310018China Key Laboratory of Complex System Modeling and Simulation Ministry of EducationHangzhou310018China Zhejiang Engineering Research Center of Data Security Governance Hangzhou310018China Intelligent Robotics Research Center Zhejiang LabHangzhou311100China HDU-ITMO Joint Institute Hangzhou Dianzi UniversityHangzhou310018China

Federated learning is a distributedmachine learningmethod that can solve the increasingly serious problemof data islands and user data privacy,as it allows training data to be kept locally and not shared with other *** trains a globalmodel by aggregating locally-computedmodels of clients rather than their ***,the divergence of local models caused by data heterogeneity of different clients may lead to slow convergence of the global *** this problem,we focus on the client selection with federated learning,which can affect the convergence performance of the global model with the selected local *** propose FedChoice,a client selection method based on loss function optimization,to select appropriate local models to improve the convergence of the global *** firstly sets selected probability for clients with the value of loss function,and the client with high loss will be set higher selected probability,which can make them more likely to participate in ***,it introduces a local control vector and a global control vector to predict the local gradient direction and global gradient direction,respectively,and calculates the gradient correction vector to correct the gradient direction to reduce the cumulative deviationof the local gradient causedby *** experiments to verify the validity of FedChoice on CIFAR-10,CINIC-10,MNIST,EMNITS,and FEMNIST datasets,and the results show that the convergence of FedChoice is significantly improved,compared with FedAvg,FedProx,and FedNova.

关键词： Federated learning model aggregation Non-IID

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Design and Evaluation of a Bidirectional Ankle Exoskeleton system

Design and Evaluation of a Bidirectional Ankle Exoskeleton S...

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Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Yiying Peng Jianyu Chen Liping Wang Jianda Han Juanjuan Zhang Tianjin Key Laboratory of Intelligent Robotics Institute of Robotics and Automatic Information System College of Artificial Intelligence and School of Materials Science and Engineering Smart Sensing Interdisciplinary Science Center Nankai University Tianjin China

Patients with foot-drop are unable to dorsiflexion during the swing phase, resulting in toe dragging and increasing the risk of falling. Ankle-foot-orthoses (AFOs) can reduce foot-drop of patients but limit their ankle plantarflexion. Assistive exoskeletons have a significant improvement on walking economy and the assistance can enhance human mobility. Here, we developed a bidirectional ankle exoskeleton to provide passive dorsiflexion assistance during the swing phase and active plantarflexion assistance during the stance phase. The performance of our exoskeleton was tested based on experiments of one healthy subject. We changed the front passive assistive materials and evaluated the kinematics and biological efforts of the subject with different assistive conditions. Results showed that the maximum ankle dorsiflexion angles were increased during the swing phase and ankle joint torques were reduced under assistance. The root mean square (RMS) of the soleus and tibialis anterior muscle activities were decreased by 21.8% and 17.9% under the assistance of elastic ropes condition. Our design expected to provide assistance for individuals with impaired dorsiflexion and plantarflexor muscle strength, which can enhance their locomotion ability.

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DOA Estimation via Adaptive Weighted Truncated Nuclear Norm

DOA Estimation via Adaptive Weighted Truncated Nuclear Norm

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Chinese Control and Decision Conference, CCDC

作者： Zhen Tian Qile Zhu Shun Fang Qi Wu Shiqian Wu Institute of Robotics and Intelligent System School of Information Science and Engineering Wuhan University of Science and Technology Wuhan China Software and Internet of Things Engineering Jiangxi University of Finance and Economics Nanchang China

Aiming at the large error of traditional direction-of-arrival (DOA) estimation algorithm caused by the low signal-to-ratio and limited sampling. This paper proposes a DOA estimation method based on adaptive weighted truncation nuclear norm. First, a new model which combines γ norm and adaptive weighted nuclear norm is proposed to accurately reconstruct the received signal covariance matrix into a low-rank covariance matrix and a sparse covariance matrix. Next, the generalized alternating direction method of multipliers (GADMM) with an adaptive stopping criterion is used to solve this convex optimization. Finally, based on the reconstructed low-rank noise-free covariance matrix, a multiple signal classification (MUSIC) algorithm is used to achieve DOA estimation. The simulation results are provided to verify the effectiveness and superiority of the proposed method.

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Nanoscale phase management of the 2D/3D heterostructure toward efficient perovskite solar cells

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science Bulletin 2024年第18期69卷 2853-2861页

作者： Hao Gu Annan Zhu Junmin Xia Wang Li Jiahao Zheng Tao Yang Shengwen Li Nan Zhang Shiliang Mei Yongqing Cai Shi Chen Chao Liang Guichuan Xing Joint Key Laboratory of the Ministry of Education Institute of Applied Physics and Materials EngineeringUniversity of MacaoMacao 999078China State Key Laboratory of Organic Electronics and Information Displays&Institute of Advanced Materials(IAM) Jiangsu National Synergetic Innovation Center for Advanced Materials(SICAM)Nanjing University of Posts&Telecommunications(NUPT)Nanjing 210023China MOE Key Laboratory for Nonequilibrium Synthesis and Modulation of Condensed Matter School of PhysicsNational Innovation Platform(Center)for Industry-Education Integration of Energy Storage TechnologyXi’an Jiaotong UniversityXi’an 710049China Ministry of Industry and Information Technology Key Lab of Micro-Nano Optoelectronic Information System Guangdong Provincial Key Laboratory of Semiconductor Optoelectronic Materials and Intelligent Photonic SystemsHarbin Institute of TechnologyShenzhen 518055China Institute for Electric Light Sources School of Information Science and TechnologyFudan UniversityShanghai 200433China

The stabilization of the formamidinium lead iodide(FAPbI_(3))structure is pivotal for the development of efficient photovoltaic *** two-dimensional(2D)layers to passivate the threedimensional(3D)perovskite is essential for maintaining the a-phase of FAPbI_(3) and enhancing the power conversion efficiency(PCE)of perovskite solar cells(PSCs).However,the role of bulky ligands in the phase management of 2D perovskites,crucial for the stabilization of FAPbI_(3),has not yet been *** this study,we synthesized nanoscale 2D perovskite capping crusts with=1 and 2 Ruddlesden-Popper(RP)perovskite layers,respectively,which form a type-Ⅱ 2D/3D *** heterostructure stabilizes the a-phase of FAPbI_(3),and facilitates ultrafast carrier extraction from the 3D perovskite network to transport contact *** introduced tri-fluorinated ligands to mitigate defects caused by the halide vacancies and uncoordinated Pb^(2+)ions,thereby reducing nonradiative carrier recombination and extending carrier *** films produced were incorporated into PSCs that not only achieved a PCE of 25.39%but also maintained 95%of their initial efficiency after 2000 h of continuous light exposure without *** findings underscore the effectiveness of a phase-pure 2D/3D heterostructure-terminated film in inhibiting phase transitions passivating the iodide anion vacancy defects,facilitating the charge carrier extraction,and boosting the performance of optoelectronic devices.

关键词： Phase-pure 2D perovskite 2D/3D heterostructure Type-II energy alignment Carrier dynamic FAPbI_(3)

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Adjacency-hopping de Bruijn Sequences for Non-repetitive Coding

arXiv

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arXiv 2023年

作者： Chen, Bin Liang, Zhenglin Wu, Shiqian The Institute of Robotics and Intelligent Systems School of Information Science and Engineering Wuhan University of Science and Technology Wuhan430081 China The Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan430072 China

A special type of cyclic sequences named adjacency-hopping de Bruijn sequences is introduced in this paper. It is theoretically proved the existence of such sequences, and the number of such sequences is derived. These sequences guarantee that all neighboring codes are different while retaining the uniqueness of subsequences, which is a significant characteristic of original de Bruijn sequences in coding and matching. At last, the adjacency-hopping de Bruijn sequences are applied to structured light coding, and a color fringe pattern coded by such a sequence is presented. In summary, the proposed sequences demonstrate significant advantages in structured light coding by virtue of the uniqueness of subsequences and the adjacency-hopping characteristic, and show potential for extension to other fields with similar requirements of non-repetitive coding and efficient matching. Copyright © 2023, The Authors. All rights reserved.

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Proposal of a novel peeling of nano-particle (PNP) process for localized material removal on a hard material surface by controllable magnetic fields 22

Proposal of a novel peeling of nano-particle (PNP) process f...

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22nd International Conference of the European Society for Precision engineering and Nanotechnology, EUSPEN 2022

作者： Permpatdechakul, Thitipat Khajornrungruang, Panart Suzuki, Keisuke Kutomi, Shotaro Graduate School of Computer Science and System Engineering Mechanical Information Science and Technology Course Kyushu Institute of Technology Fukuoka Japan Department of Intelligent and Control Systems Avanced Mechanical Division Kyushu Institute of Technology Fukuoka Japan School of Computer Science and System Engineering Advanced Mechanical Course Kyushu Institute of Technology Fukuoka Japan

ISBN: (纸本)9781998999118

This article proposes a novel Peeling of Nano-Particle (PNP) process to locally remove material on a hard material surface using controllable magnetic fields. Fe3O4 particles in the size range of 50-100 nm in aqueous solution (pH value 11 adjusted by KOH) were magnetically controlled to adhere and remove from a 4H-SiC surface by two electromagnetic coils, which were sandwiched between the substrate. The particle controlling phenomenon on the surface was experimentally observed and verified by our developed apparatus applying an evanescent field. According to the results, particles could be controlled to approach and remove from the substrate surface with 12mT of magnetic field at the selective area on the substrate surface to realise the proposed PNP process. © European Society for Precision engineering and Nanotechnology, Conference Proceedings - 22nd International Conference and Exhibition, EUSPEN 2022. All rights reserved.

关键词： Magnetic fields

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