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Three-Dimensional Refractive Index Estimation Based on Non-interferometric Optical Diffraction Tomography with Angular and Axial Illumination Scanning

Three-Dimensional Refractive Index Estimation Based on Non-i...

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Digital Holography and Three-Dimensional Imaging, DH 2024

作者： Bazow, Brad Raub, Christopher B. Nehmetallah, George Departments of Electrical Engineering and Computer Science The Catholic University of America 620 Michigan Avenue N.E. WashingtonDC20064 United States The Johns Hopkins University Applied Physics Laboratory 11100 Johns Hopkins Road LaurelMD20723 United States Departments of Biomedical Engineering The Catholic University of America 620 Michigan Avenue N.E. WashingtonDC20064 United States

We present computational inverse scattering to achieve three-dimensional refractive index reconstructions of biological specimens with sub-micron resolution in an optical diffraction tomography system with angular and...

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Adaptive position tracking control of the lower limb exoskeleton robot with an uncertain dynamic model 18

Adaptive position tracking control of the lower limb exoskel...

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18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023

作者： Yuan, Ting Zhang, Chi Yi, Feng Lv, Pingping Li, Shupei Zhang, Meitong Ningbo University Ningbo Instituteof Materials Technology and Engineering Chinese Academy of Sciences Faculty of Electrical Engineering and Computer Science Ningbo315201 China Chinese Academy of Sciences Zhejiang Key Laboratory of Robotics and Intelligent Manufacturing Equipment Technology Ningbo Institute of Materials Technology and Engineering Ningbo315201 China University of Chinese Academy of Sciences Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences College of Materials Science and Opto-Electronic Technology Ningbo315201 China Hebei University of Science and Technology Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences School of Electrical Engineering Ningbo315201 China

ISBN: (纸本)9798350312201

In this paper, an adaptive position control method combining proportional-derivative (PD) control, RBF neural network-based sliding mode (SM) control, and feedforward (FF) control, i.e., PD-FF-SM control, is proposed to deal with the dynamic uncertainties, disturbances, and slow response in lower limb exoskeleton robot system. The Lagrange method is utilized to establish dynamic models that ignore the uncertainties and disturbances in the swing phase and supporting phase. Then, the PD feedback controller is designed with a sliding surface function, to keep the system stable. The FF controller is adopted to improve the response by using dynamic models. And the RBF neural network-based SM controller is designed to compensate for the uncertainties and disturbances. The system's stability is verified by Lyapunov's theorem. The simulation results show that the proposed control method can effectively reduce the error of position tracking and response time with inaccurate dynamic modeling. © 2023 IEEE.

关键词： Sliding mode control

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Enhancing Remote Sensing Image Classification Using Arithmetic Optimization Algorithm with Deep Learning Approach

Enhancing Remote Sensing Image Classification Using Arithmet...

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International Conference on Advances in Information Technology (ICAIT)

作者： R. Shanthi Balasubramaniam D R. Venkatesh C. Sankari V. Manimaran Shaik Hedayath Basha Department of computer applications Faculty of science and humanities SRM Institute of science and Technology Chengalpattu Tamilnadu Department of Biomedical Engineering VelTech Rangarajan Dr Sagunthala R & D Institute of Science and Technology Chennai Computer Science and Engineering Ramco Institute of Technology Rajapalayam Electrical and Electronics Engineering Chennai Institute of Technology Department of Computer Science and Engineering Kongu Engineering College Erode Tamilnadu Department of ECE R.M.K. College of Engineering and Technology

ISBN: (数字)9798350383867

ISBN: (纸本)9798350383874

The classification of Remote sensing image (RSI)is a vital task in field of geospatial analysis where aerial or satellite images are classified into predefined classes or land cover sorts. It plays a main part in diverse fields namely agriculture, disaster management, environmental surveillance, urban planning, and natural resource management. With the machine learning (ML) and deep learning (DL) models, these images examined and categorized depending on their spatial, spectral and temporal features. The exact detection of remote sensing images simplifies decision-making procedures, aiding governments, environmental agencies, and companies to make knowledgeable decisions and policies. It authorizes experts to observe variations in lands, discover land use trends, and evaluate environmental effects and making it a vital device in addressing present difficult challenges connected to weather change, urban development, and natural resource protection. This study presents an enhanced remote sensing image classification utilizing arithmetic optimization algorithm with DL (ERSC-AODL) Approach. The ERSC-AODL technique concentrates on the accurate recognition of the RSI into dissimilar classes. It begins with the use of an EfficientNet feature extractor, which derives complex spectral and spatial data, and acts as a base of proper representation of the images. Moreover, the recognition process takes place by a bidirectional long short-term memory (BiLSTM). Finally, the hyperparameter optimization procedure is performed by the ERSC-AODL technique. To portray the proficient classification outputs of the ERSC-AODL technique, a range of experiments were utilized. The investigational outputs stated that the ERSC-AODL technique attains improved accomplishment over other models.

关键词： Natural resources Recurrent neural networks Feature extraction Spatial databases Classification algorithms Data mining Remote sensing Optimization Long short term memory Image classification

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Classification of skin lesions using morpho-granulometry features derived from color clusters

Classification of skin lesions using morpho-granulometry fea...

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International Conference on System Theory, Control, and Computing (ICSTCC)

作者： Gigi Tăbăcaru Simona Moldovanu Marian Barbu Department of Automatic Control and Electrical Engineering Faculty of Automation Computers Electrical Engineering and Electronics "Dunarea de Jos" University of Galati Galati Romania Computer Science and Information Technology Faculty of Automation Computers Electrical Engineering and Electronics The Modelling & Simulation Laboratory "Dunarea de Jos" University of Galati Galati Romania

ISBN: (数字)9798350364293

ISBN: (纸本)9798350364309

The skin lesion can be thought of as a biological system, so the morpho-granulometry of significant color clusters found in skin lesions is one of the elements that reproduce in a natural way the structure of the lesion, this novelty is highlighted in this study. Important features of skin lesions can be modulated by fusing neural networks (NN) and machine learning (ML). By choosing the nevus and melanoma classes, the primary goal was accomplished, and three databases were used to test the methodology. The characteristics based on morpho-granulometry allowed for the identification of microstructure within the images, which can be very helpful in characterizing the biological system. Based on random forest (RF) and extreme gradient boosting (XGboost) classifiers, this work aimed to improve the classification performance of important feature selection. The selected features from three free image databases with three NNs were classified. In a binary classification of nevus vs. melanoma, the results showed that the pattern recognition neural network (PRNN), according to the PH2 database, provided an accuracy of 0.923 and an F1-score of 0.876. The classification is interpretable if it is not validated. In our study, the best results were verified with a logistic regression (LR) classifier.

关键词： Accuracy Recurrent neural networks Image color analysis Melanoma Biological systems Artificial neural networks Feature extraction Skin Lesions Classification tree analysis

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Automated Deep Learning Pipeline for Accurate Segmentation of Aortic Lumen and Branches in Abdominal Aortic Aneurysm: A Two-Step Approach

Automated Deep Learning Pipeline for Accurate Segmentation o...

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Intelligent Methods, Systems, and Applications (IMSA)

作者： Fatma N. Hassan Ahmed M. Mahmoud Ahmed F. Elnokrashy Ashraf Y. Hassan Department of Electrical Engineering Benha Faculty of Engineering Benha University Benha Egypt Department of Biomedical Engineering and Systems Cairo University Giza Egypt Astute Imaging Kirkland WA US Department of Computer Science Technology and Computer Science Nile University Giza Egypt Benha University Benha Egypt

ISBN: (数字)9798350362633

ISBN: (纸本)9798350362640

Abdominal Aortic Aneurysm (AAA) is a serious medical condition characterized by the abnormal enlargement of the abdominal aorta. If left untreated, AAA can have life-threatening consequences. Accurate segmentation of the aorta in Computed Tomography Angiography (CTA) images plays a vital role in treatment planning for AAA. However, manual and semi-automatic segmentation methods suffer from limitations in terms of time and accuracy. This study presents a deep learning pipeline that aims to fully automate the precise and efficient segmentation of the aorta and its branches within CTA images. A two-step approach is proposed for the segmentation of the aorta and its branches in contrast-enhanced CTA scans. The first step involves utilizing a UNet++ model to perform aortic segmentation across the entire set of CTA axial slices. In the second step, a post processing algorithm is employed to track the continuity of the segmented aorta while effectively discarding false positive (FP) objects. The assessment of the fully automated method revealed remarkable outcomes, with a mean Dice coefficient of 0.941 on a test set consisting of 10 CTA scans. The automated segmentation results are utilized to create a comprehensive 3D model. The study results indicate that the utilization of the proposed deep learning-based pipeline is highly effective in achieving accurate segmentation of the aortic lumen and its branches. The practical implications of this approach extend to pre-operative planning. This highlights the valuable contribution of the proposed method in improving the management and treatment of patients diagnosed with aortic aneurysm.

关键词： Image segmentation Solid modeling Accuracy Three-dimensional displays Pipelines Surgery Aneurysm

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Nonlinear PID DC-link Voltage Control for Hybrid Power Filter Based on Robust Exact Differentiator with Improved Transient Response 48

Nonlinear PID DC-link Voltage Control for Hybrid Power Filte...

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48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022

作者： Gong, Cheng Sou, Wai-Kit Lam, Chi-Seng Komurcugil, Hasan State Key Laboratory of Analog and Mixed-Signal Vlsi University of Macau China University of Macau Institute of Microelectronics China University of Macau Faculty of Science and Technology Department of Electrical and Computer Engineering China Eastern Mediterranean University Department of Computer Engineering Famagusta Turkey

ISBN: (数字)9781665480253

ISBN: (纸本)9781665480253

LC-coupling hybrid active power filter (LC-HAPF) is a cost-effective solution to address power quality issues in low and medium voltage distribution networks. The DC-link voltage controller plays an important role of the LC-HAPF performance. Conventionally, proportional-integral (PI) controller is commonly used for DC-link voltage control due to the ideally zero steady-state error. However, the property of integrator slows down the transient response of DC-link voltage and thus effects the LC-HAPF dynamic performance. In this paper, a nonlinear PID (NPID) controller based on robust exact differentiator (RED) is proposed to improve the transient response of conventional PI controller. First, the parameters of the PID controller are designed by s-domain transfer function analysis. Then, the RED is proposed to replace the linear differentiator, which provides the differential signal fast and accurately. Finally, the advantages of the proposed NPID controller based on RED are verified by simulation results compared with the conventional PI controller. © 2022 IEEE.

关键词： Transient analysis

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Visualizing Code Syntax: Empowering Developers with a Global View for Enhanced Code Quality Evaluation

Visualizing Code Syntax: Empowering Developers with a Global...

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International Conference on Advanced computer Theory and engineering, ICACTE

作者： Chaima Adjel Fadila Atil Djamel Meslati Computer science departement Faculty of Electrical Engineering and Computing Laboratory LISCO University Badji Mokhtar-Annaba Annaba Algeria

This article discusses the issues that come with system evolution, specifically the challenges of comprehending and maintaining old code created by unreachable developers. In this instance, we want to highlight the value of using code visualization to get a global perspective of the components and their dependencies, since this can assist in recognizing any possible structural problems. Additionally, visualization can shed light on the code's scalability and performance properties. A well-written program with clear syntax that respects low coupling and separation of concerns makes system maintenance and evolution easier, which saves time and money. Adopting a scalable and flexible language also makes maintenance and development smoother. In this paper, we made a visualization of Mage code in order to evaluate its syntax flexibility and scalability.

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A highly integrated flexible array non-contact ECG sensing electrode based on FPC

A highly integrated flexible array non-contact ECG sensing e...

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6th International Conference on Intelligent Computing and Signal Processing (ICSP)

作者： Gang Wu Kaikai Wang Baoliang Feng Binjun Shi Zhen Liu Guokun Zuo Changcheng Shi Faculty of Electrical Engineering & Computer Science Ningbo University Ningbo China Ningbo Institute of Materials Technology & Engineering CAS Ningbo China Ningbo Cixi Institute of Biomedical Engineering Ningbo China

The existing array non-contact ECG sensing technology mostly uses rigid electrode or conductive fabric electrode, in which the rigid electrode is too hard to make the electrode difficult to close to the human body well, and the conductive fabric electrode is too soft to cause the electrodes to be wrinkled, both of which will lead to poor ECG signal quality. In order to overcome the problem that it is difficult to obtain high-quality ECG signals due to electrode materials, this study combined the manufacturing process of Flexible Printed Circuit (FPC) with the surface treatment process of Electroless Nickel/Immersion (ENIG) and adopted polyimide (PI) and rolled copper as electrode materials, which makes the array electrode electrodes extremely flexible, tough, and flat. At the same time, in terms of electrode design, the test and verification of the electrode unit also ensured the rationality of the array electrode. Subsequently, the electrode was verified by electrode test and human experiment, and the results showed that the electrode could receive ECG signals well, and compared with the ECG signals obtained by the traditional Ag/AgCl electrodes, the signal-to-noise ratio (SNR) of the signals obtained by the two types of electrodes reached above 38 dB and the waveform characteristics were highly consistent.

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Sliding Mode Control of the PUMA 560 Robot

Sliding Mode Control of the PUMA 560 Robot

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2023 International Conference on Control, Automation and Diagnosis, ICCAD 2023

作者： Fekik, Arezki Azar, Ahmad Taher Hamida, Mohamed Lamine Denoun, Hakim Kais, Dyhia Saidi, Sabrina Mohand Bousbaine, Amar Kamal, Nashwa Ahmad Al Mhdawi, Ammar K. Njima, Chakib Ben Department of Electrical Engineering University Akli Mohand Oulhadj-Bouria Rue Drissi Yahia Algeria Algeria Riyadh Saudi Arabia College of Computer & Information Sciences Prince Sultan University Riyadh Saudi Arabia Benha University Faculty of Computers and Artificial Intelligence Egypt Mouloud Mammeri University L2CSP Laboratory Department of Electrical Engineering Algeria University of Derby College of Science and Engineering United Kingdom Cairo University Faculty of Engineering Giza Egypt Edge Hill University United Kingdom University of Sousse Tunisia

ISBN: (纸本)9798350347074

The purpose of this article is to present the application of the sliding mode control and investigate its effectiveness when applied to a three-dimensional robotic manipulator model. The analysis is based on the application of the sliding mode control law for the PUMA 560 model, three degrees of freedom, through the development of a dynamic simulation model. The simulation results show the effectiveness of this proposed method for the automation of industrial applications, such as assembly, machining (deburring, trimming), and surface tracking (polishing). This technique provides a useful insight into the advantages of using sliding mode control laws in robotics applications. © 2023 IEEE.

关键词： Sliding mode control

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Integrating Sustainability and Industry 4.0: A Framework for Sustainable Logistics 4.0

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Circular Economy and Sustainability 2025年第3期5卷 2157-2195页

作者： Di Nardo, Mario Gallab, Maryam Murino, Teresa Wu, Jing Pandey, Shatrudhan Facoltàdi Ingegneria Università Telematica Pegaso Rome 00186 Italy MIS-LISTD Laboratory Computer Science Department Mines-Rabat School (ENSMR) Rabat 10000 Morocco Department of Chemical Materials and Industrial Production Engineering University of Naples “Federico II” Naples Italy Department of Electrical and Photonics Engineering Technical University of Denmark Kgs. Lyngby 2800 Denmark Marwadi University Research Center Faculty of Management Studies Marwadi University Gujarat Rajkot 360003 India

As society becomes more aware of environmental and social issues, supply chain stakeholders increasingly consider these factors alongside efficiency, cost, and time. The logistics industry must adapt by integrating Industry 4.0 technologies and sustainability practices. Sustainable Logistics 4.0, though nascent, is gaining traction for enhancing sustainability through digital interventions. This study conducted a comprehensive literature review and bibliometric network analysis using data extracted from the Scopus and Google Scholar databases, covering the period from 2013 to 2023, focusing on the integration of sustainability, Industry 4.0, and logistics. Noting a gap in conceptual frameworks, the paper performs a SWOT analysis to identify key factors and proposes a framework for digitalizing sustainable logistics and addressing emerging challenges. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

关键词： Circular Economy Industry 4.0 Logistics Sustainability TBL

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