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2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2023

作者： Anselmi, Nicola Rosatti, Pietro Tosi, Luca Zardi, Francesco Rocca, Paolo Toso, Giovanni Massa, Andrea DICAM - Department of Civil Environmental and Mechanical Engineering Trento38123 Italy Xi'an710071 China European Space Agency Radio Frequency Payloads and Technology Division Noordwijk2200 AG Netherlands Haidian Beijing100084 China School of Electronic Science and Engineering Chengdu611731 China

ISBN: (纸本)9781665442282

The design of modular phased arrays for satellite systems is addressed. The array architecture is simplified through an irregular tiling technique where the number of transmit/receive modules is reduced by using a single output/input for all the radiating elements clustered in a tile. An illustrative example is shown to demonstrate the possibility of using tiled arrays for space applications when considering a domino-like shaped tile. © 2023 IEEE.

关键词： Space applications

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The Effect of Disturbances on Plant-Model Mismatch Detection using the Plant-Model Ratio: A Surge Tank Case Study

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IFAC-PapersOnLine 2024年第22期58卷 24-29页

作者： Heinz K. Mittermaier Johan D. le Roux Ian K. Craig Measurement and Control Division Mintek Randburg South Africa. Department of Electrical Electronic and Computer Engineering University of Pretoria Pretoria South Africa.

The surge tank in a bulk tailings treatment plant aims to reject flow and density disturbances. However, for large disturbances, there may be an inversion in the gain between the water inflow and tank slurry density for a linearized model of the plant. The plant-model ratio (PMR) is a method to diagnose model-plant mismatch (MPM), such as gain-inversion, in the absence of disturbances. This article evaluates the influence of disturbances on the ability of the PMR to diagnose MPM for the surge tank. If the disturbance is measured, as in the case of the surge tank, the PMR is able to detect MPM such as gain-inversion. A controller can be adapted according to the MPM information from the PMR diagnosis.

关键词： Controller performance monitoring model predictive control model-plant mismatch process performance monitoring surge tank

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Adaptive optics two photon microscopy enables in vivo longitudinal visualization of the glaucoma progression with subcellular resolution in the mouse model 34

Adaptive optics two photon microscopy enables in vivo longit...

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Ophthalmic Technologies XXXIV 2024

作者： Fu, Yiming Pham, Binh Minh He, Sicong Qin, Zhongya Xie, Ting Qu, Jianan Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong Division of Life Science Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong Department of Biomedical Engineering Southern University of Science and Technology Guangdong Province Shenzhen China

ISBN: (纸本)9781510669079

Glaucoma is characterized by the irreversible retinal ganglion cells (RGCs) loss and has received great research and clinical attention due to its complex mechanism and loss of effective treatment. Longitudinal in vivo study on glaucoma in mouse model can be a promising approach to unveil the mechanism of glaucoma. In this paper, we use a silicon oil (SO) induced glaucoma model on mouse and the adaptive optics two photon microscope system to evaluate whether the aberration from both mouse eye and SO can be corrected and then longitudinal imaging with subcellular resolution on the mouse retina can be achieved. © 2024 SPIE.

关键词： Adaptive optics

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Efficient Resource Allocation Framework for Network Slicing-enabled Open RAN

Efficient Resource Allocation Framework for Network Slicing-...

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International Conference on Communications and electronics, ICCE

作者： Tuan-Vu Truong Quang-Trung Luu Van-Dinh Nguyen College of Engineering and Computer Science & Center for Environmental Intelligence VinUniversity Hanoi Vietnam School of Electrical and Electronic Engineering Hanoi University of Science and Technology Hanoi Vietnam

ISBN: (数字)9798350379792

ISBN: (纸本)9798350379808

The transition to 5G technology has revolutionized cellular networks, leading to an unprecedented demand for high-bandwidth and low-latency services. To meet these evolving demands, next-generation mobile networks are turning to innovative solutions such as network slicing within the open radio access network (RAN) architecture. This paper focuses on addressing the challenges associated with dynamic virtual network function (VNF) mapping and resource allocation in terms of both communication and computing resources. The ultimate goal is to simultaneously maximize the total reward for admitted slices and minimize the associated cost by allocating resources to the Open RAN slices catering to diverse service types. To efficiently solve the formulated problem, we decompose it into two sub-problems tailored to different timescales which are executed at the different layers within the Open RAN architecture. To solve the non-convex long-term problem, we first transform it to a more tractable form and employ the successive convex approximation (SCA) method to achieve at least a locally optimal solution. Numerical simulations demonstrate the efficacy and quick convergence of the proposed algorithm, highlighting its potential to improve network slicing performance and support diverse applications in future wireless networks.

关键词： Costs Network slicing Wireless networks Open RAN computer architecture Transforms Numerical simulation

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RetinaStereo: Dynamic-Volume Stereo Matching Network

RetinaStereo: Dynamic-Volume Stereo Matching Network

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Xiaoyan Liao Haoliang Zhao Fan Yang Kwokching Cheung Jun Jiang Yong Zhao Jie Chen Xinan Wang School of Electronic and Computer Engineering Shenzhen Graduate School Peking University Shenzhen China Department of Civil and Environmental Engineering The Hong Kong Polytechnic University Hong Kong China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Existing stereo matching techniques often struggle with detailing subtle objects on depth edges. To alleviate this problem, we introduced the Dynamic-Range Disparity Initialization module, which integrates three complementary branches: the dynamic dense volume for localized disparity sampling, the sparse global volume for encoding search center information, and the background static volume with skip connections for enhancing depth edge accuracy. The dynamic dense volume identifies optimal search centers for each pixel and performs local neighborhood sampling for cost aggregation, thereby generating the initial disparity map. Since the search center positions get lost while assembling the disparity samples, a sparse global volume is proposed to implicitly encode these positions during the training process of the network. We also designed the Inception Update module based on our analysis of convolutional structures and nonlinear gating mechanisms. RetinaStereo achieves state-of-the-art performance on the KITTI-2015 leaderboard for the D1-fg metric among published methods.

关键词： Training Measurement Accuracy Costs Correlation Convolution Search problems Encoding Acoustics Speech processing

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EOG acquisition system based on ATmega AVR microcontroller

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Journal of Ambient Intelligence and Humanized Computing 2023年第12期14卷 16589-16605页

作者： Abdel-Samei, Abdel-Gawad A. Shaaban, Abdel-Salam Brisha, Ayman M. El-Samie, Fathi E. Abd Ali, Ahmed S. Department of Electronics Technology Faculty of Technology and Education Beni-Suef University Beni-Suef Egypt Department of Process of Control Technology Faculty of Technology and Education Beni-Suef University Beni-Suef Egypt Department of Mechanical Engineering Mechatronics Division Faculty of Engineering Assiut University Assiut Egypt Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

This paper presents a hardware and software of an electrooculogram (EOG) acquisition system based on ATmega AVR microcontroller for the acquisition of vertical and horizontal eye movements. The presented system is used to acquire a dataset of eye movements for volunteers. This system gives two channels representing vertical and horizontal EOG signals. The frequency range of the EOG signal is known to be 0.1 to 10 Hz, and hence this frequency range is isolated with a High-Pass Filter (HPF) with a cutoff frequency of 0.1 Hz followed by a Low-Pass Filter (LPF) with a cutoff frequency of 10 Hz. The EOG acquisition system is interfaced with an ATmega AVR microcontroller to acquire a dataset that can be used for controlling hardware such as Light Emitting Diodes (LEDs), wheelchair, and robot arm. The presented system is composed of EOG signal acquisition, Ag/AgCl electrodes, analog-to-digital converter through Arduino Mega 2560 board microcontroller unit, trainer board, laptop, keypad, and Liquid Crystal Display (LCD). The eye movement is detected by measuring the potential difference between cornea and retina using five Ag–Agcl disposable electrodes. Different volunteers of different ages at different times have been treated with the presented system to obtain data. Classified vertical and horizontal EOG signals and the basic eye movements e.g., open eye, left, right, up, and down can be used to control robots and wheelchairs for rehabilitation purposes. © 2023, The Author(s).

关键词： Electrodes

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Commercial Indian Bamboo Species Classification on matK DNA Barcode Sequences using Machine Learning Techniques with K-mer

Commercial Indian Bamboo Species Classification on matK DNA ...

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2023 International Conference on computer, electronics and Electrical engineering and their Applications, IC2E3 2023

作者： Sawarkar, Ankush D. Shrimankar, Deepti D. Singh, Lal Agrahari, Anurag Lachure, Sagar Bokde, Neeraj Dhanraj Department of Computer Science and Engineering Maharashtra Nagpur440 010 India Environmental Biotechnology and Genomics Division Maharashtra Nagpur440 020 India Aarhus University Center for Quantitative Genetics and Genomics Aarhus Denmark

ISBN: (纸本)9798350338003

Bamboo, a grass, belongs to the Poaceae family, with 1642 species from 116 genera worldwide. It has exceptional physical, chemical, and mechanical qualities, which allow it to be employed in over a thousand different ways and contribute to a trade value of USD 2.76 billion. Bamboo is grown using rhizomes, tissue culture, or short branch cuttings without any other checks resulting in incorrect species identification and categorisation. Therefore, the classification or identification of these bamboo use its DNA barcode sequences with a K-mer based method, and machine learning (ML) is the most excellent strategy for resolving issues with the conventional or traditional categorisation of the species. A DNA barcode is a brief genetic signature that helps identify the species to which an organism belongs. It is possible to extract a useful feature from genome sequences using K-mer based approaches, which may then be used to increase comparison accuracy. In this research, we evaluate the classification performance of four supervised ML models on the DNA-barcode sequence of six Indian commercial bamboo species with a different K-mer combination. For this classification, we choose matK barcode region and supervised ML models such as Logistic Regression (LR), Random Forest (RF), Support Vector Machine (SVM) and Gradient Boosting Machine (GBM). The results analysis of these models on the matK DNA sequence with different K-mers demonstrates that the classification capabilities of the GBM approaches are quite promising, and it has an accuracy of 95.3% on average. © 2023 IEEE.

关键词： DNA

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Three-Dimensional Shear Wave Elastography Using a 2D Row Column Addressing(RCA)Array

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Biomedical engineering Frontiers 2022年第1期3卷 337-347页

作者： Zhijie Dong Jihun Kim Chengwu Huang Matthew RLowerison U-Wai Lok Shigao Chen Pengfei Song Beckman Institute for Advanced Science and Technology University of Illinois Urbana-ChampaignUrbanaILUSA Department of Electrical and Computer Engineering University of Illinois Urbana-ChampaignUrbanaILUSA Division of ICT Convergence Engineering/Major in Electronic Engineering Kangnam UniversityRepublic of Korea Department of Radiology Mayo Clinic College of Medicine and ScienceRochesterMNUSA

*** develop a 3D shear wave elastography(SWE)technique using a 2D row column addressing(RCA)array,with either external vibration or acoustic radiation force(ARF)as the shear wave *** *** proposed method paves the way for clinical translation of 3D SWE based on the 2D RCA,providing a low-cost and high volume rate solution that is compatible with existing clinical *** is an established ultrasound imaging modality that provides a direct and quantitative assessment of tissue stiffness,which is significant for a wide range of clinical applications including cancer and liver *** requires high frame rate imaging for robust shear wave *** to the technical challenges associated with high volume rate imaging in 3D,current SWE techniques are typically confined to *** SWE from 2D to 3D is significant because of the heterogeneous nature of tissue,which demands 3D imaging for accurate and comprehensive ***.A 3D SWE method using a RCA array was developed with a volume rate up to 2000 *** performance of the proposed method was systematically evaluated on tissue-mimicking elasticity phantoms and in an in vivo case ***.3D shear wave motion induced by either external vibration or ARF was successfully detected with the proposed *** 3D shear wave speed maps were reconstructed for phantoms and in *** high volume rate 3D imaging provided by the 2D RCA array provides a robust and practical solution for 3D SWE with a clear pathway for future clinical translation.

关键词： Shear elasticity typically

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DB-DCAFN:dual-branch deformable cross-attention fusion network for bacterial segmentation

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Visual Computing for Industry,Biomedicine,and Art 2023年第1期6卷 155-170页

作者： Jingkun Wang Xinyu Ma Long Cao Yilin Leng Zeyi Li Zihan Cheng Yuzhu Cao Xiaoping Huang Jian Zheng School of Biomedical Engineering(Suzhou) Division of Life Sciences and MedicineUniversity of Science and Technology of ChinaHefei 230026China Suzhou Institute of Biomedical Engineering and Technology Chinese Academy of SciencesSuzhou 215163China Department of Infectious Diseases the First Affiliated Hospital of Soochow UniversitySuzhou 215006China Institute of Biomedical Engineering School of Communication and Information EngineeringShanghai UniversityShanghai 200444China College of Computer and Information Hohai UniversityNanjing 210098China School of Electronic and Information Engineering Changchun University of Science and TechnologyChangchun 130022China Jinan Guoke Medical Technology Development Co. LtdJinan 250101China

Sputum smear tests are critical for the diagnosis of respiratory diseases. Automatic segmentation of bacteria from spu-tum smear images is important for improving diagnostic efficiency. However, this remains a challenging task owing to the high interclass similarity among different categories of bacteria and the low contrast of the bacterial edges. To explore more levels of global pattern features to promote the distinguishing ability of bacterial categories and main-tain sufficient local fine-grained features to ensure accurate localization of ambiguous bacteria simultaneously, we propose a novel dual-branch deformable cross-attention fusion network (DB-DCAFN) for accurate bacterial segmen-tation. Specifically, we first designed a dual-branch encoder consisting of multiple convolution and transformer blocks in parallel to simultaneously extract multilevel local and global features. We then designed a sparse and deformable cross-attention module to capture the semantic dependencies between local and global features, which can bridge the semantic gap and fuse features effectively. Furthermore, we designed a feature assignment fusion module to enhance meaningful features using an adaptive feature weighting strategy to obtain more accurate segmentation. We conducted extensive experiments to evaluate the effectiveness of DB-DCAFN on a clinical dataset comprising three bacterial categories: Acinetobacter baumannii, Klebsiella pneumoniae, and Pseudomonas aeruginosa. The experi-mental results demonstrate that the proposed DB-DCAFN outperforms other state-of-the-art methods and is effective at segmenting bacteria from sputum smear images.

关键词： Bacterial segmentation Dual-branch parallel encoder Deformable cross-attention module Feature assignment fusion module

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Architecture for AI-Based Validation of Wastewater Management Using Open Data Exchange Technique

Architecture for AI-Based Validation of Wastewater Managemen...

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2023 International Conference on Circuit Power and Computing Technologies, ICCPCT 2023

作者： William, P. Oyebode, Oluwadare Joshua Ramu, Gandikota Gupta, Manish Alzubaidi, Laith H. Srivastava, Arun Pratap Sanjivani College of Engineering Savitribai Phule Pune University Department of Information Technology Pune India Afe Babalola University Civil and Environmental Engineering Ekiti State Ado-Ekiti Nigeria Institute of Aeronautical Engineering Department of Computer Science and Engineering Hyderabad500043 India Lovely Professional University Division of Research and Development Phagwara India The Islamic University Faculty of Engineering Najaf Iraq Lloyd Institute of Engineering and Technology Department of CSE Uttar Pradesh Greater Noida201308 India

ISBN: (纸本)9798350333244

To processing plant-wide data, it is not uncommon for there to be issues with sensors. Some examples of these issues include sensor failures, sensor calibration difficulties, sensor fouling and blockage, and connection problems between sensors, actuators, and the data management system. These problems may have an effect on the quality of the data, which will make it more difficult to implement sophisticated data-driven monitoring and control of (crucial) water operations. A method for the intelligent validation of data is provided in this article. The sensor data coming from a wastewater treatment plant are validated and verified by this process. The application for data validation has been integrated, tested, and put into production at the water utility known as Water Net. The method of validation is predicated on an anomaly detector that, in the event that an anomaly is found, combines (statistical) threshold-based procedures, (AI-based) autoencoder model predictions, and a component for data reconciliation. This occurrence repeats itself whenever an anomaly of some kind is found. In spite of the signal's volatility, the autoencoder models displayed outstanding levels of accuracy and great reconciliation performance. In addition, signals for both verified and raw data are provided in a way that is extremely near to real time to a dashboard. This keeps the dashboard up to date with the most recent information. Validated data may also be utilized as a screening tool for data that is being ingested by another AI-based model in order to monitor and intelligently manage the wastewater treatment plant, as well as to minimize greenhouse gas emissions and energy consumption while maintaining effluent water quality requirements. These goals may be accomplished while still meeting all applicable criteria. If this were done, it would be in compliance with the regulations for maintaining the effluent water's quality. © 2023 IEEE.

关键词： Wastewater treatment

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