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Microsphere-assisted quantitative phase microscopy:a review

Light(Advanced Manufacturing) 2024年第1期5卷 131-150页

作者： Vahid Abbasian Tobias Pahl Lucie Hüser Sylvain Lecler Paul Montgomery Peter Lehmann Arash Darafsheh Department of Radiation Oncology Washington University School of Medicine in St.LouisSt.LouisMO 63110USA Imaging Science Program McKelvey School of EngineeringWashington University in St.LouisSt.LouisMO 63130USA Measurement Technology Group Faculty of Electrical Engineering and Computer ScienceUniversity of KasselWilhelmshöher Allee 7134121 KasselGermany ICube Research Institute INSA StrasbourgUniversitéde StrasbourgCNRS67000 StrasbourgFrance

Light microscopes are the most widely used devices in life and material sciences that allow the study of the interaction of light with matter at a resolution better than that of the naked *** microscopes translate the spatial differences in the intensity of the reflected or transmitted light from an object to pixel brightness differences in the digital ***,a phase microscope converts the spatial differences in the phase of the light from or through an object to differences in pixel *** microscopy,a phase-based approach,has found application in various *** interferometry has brought nanometric axial resolution,the lateral resolution in quantitative phase microscopy(QPM)has still remained limited by diffraction,similar to other traditional microscopy *** the resolution has been the subject of intense investigation since the invention of the microscope in the 17th *** the past decade,microsphere-assisted microscopy(MAM)has emerged as a simple and effective approach to enhance the resolution in light *** can be integrated with QPM for 3D label-free imaging with enhanced ***,we review the integration of microspheres with coherence scanning interference and digital holographic microscopies,discussing the associated open questions,challenges,and opportunities.

关键词： Phase microscopy Digital holographic microscopy Microsphere Resolution

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3D-to-2D-to-3D Conscious Learning

3D-to-2D-to-3D Conscious Learning

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2022 IEEE International Conference on Consumer Electronics, ICCE 2022

作者： Weng, Juyang Department of Computer Science and Engineering Michigan State University East LansingMI48824 United States Cognitive Science Program Michigan State University East LansingMI48824 United States Neuroscience Program Michigan State University East LansingMI48824 United States Brain-Mind Institute OkemosMI48864 United States GENISAMA OkemosMI48864 United States

ISBN: (纸本)9781665441544

This is a theoretical paper on conscious learning for thoughts and creativity through general-purpose and autonomous imitation of demonstrations. This conscious learning is end-to-end (3D-to-2D-to-3D) and free from annotations of 2D images and 2D motor images (e.g., a bounding box to be attended to). The conscious learning algorithm directly takes that of the Developmental Networks that has been previously published extensively with rich experimental results. Apparently, humans and animals do this type of fully automated learning daily, but it is unclear a robot can do the same. Recently, [1], [2] presented a theory of conscious learning rooted in emergent universal Turing machines. It appeared to be the first algorithmic level theory of holistic consciousness, other than many papers in the literature about piecemeal consciousness. However, [1], [2] proved only conscious learning in motor-imposed training mode, namely 3D-to-2D taught by 2D motor impositions, free from 2D annotations. This paper fills the challenging gap in [1], [2] so the conscious learning is 3D-to-2D-to-3D (end-to-end) without motor-impositions or computing 'inverse kinematics'. This is a major departure from traditional AI-handcrafting symbolic labels that tend to be brittle (e.g., for driverless cars) and then 'spoon-feeding' pre-collected 'big data'. Autonomous imitations drastically reduce the teaching complexity compared to pre-collected 'big data', especially because no annotations of training data are needed. Furthermore, conscious learning allows creativity beyond what is taught. This work is directly related to consumer electronics because it requires large-scale on-the-fly brainoid chips in future wearable robots/devices for consumers. © 2022 IEEE.

关键词： Big data

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Characteristic Mode Analysis of Nanostructures using Hydrodynamic Volume Integral Equation

Characteristic Mode Analysis of Nanostructures using Hydrody...

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Antennas and Propagation & USNC/URSI National Radio science Meeting

作者： Meruyert Khamitova Ran Zhao Doolos Aibek uulu Hakan Bagci Electrical and Computer Engineering (ECE) Program Computer Electrical and Mathematical Science and Engineering (CEMSE) Division King Abdullah University of Science and Technology (KAUST) Thuwal Kingdom of Saudi Arabia School of Electronic Science and Engineering University of Electronic Science and Technology of China (UESTC) Chengdu Sichuan China Department of Mathematics and Natural Sciences University of Central Asia (UCA) Naryn Kyrgyzstan

ISBN: (数字)9798350369908

ISBN: (纸本)9798350369915

The characteristic mode analysis (CMA) is formulated and implemented for the hydrodynamic volume integral equation (HDVIE) that is used to mathematically model electromagnetic field interactions and conduction current dynamics on nanoantennas and nanoscatterers. The proposed method produces excitation-independent characteristic hydrodynamic currents and the corresponding modal significance curves, providing useful information that can be used to optimize the performance of a nanoantenna. Numerical results demonstrate the reliability and the applicability of the proposed approach.

关键词： Solid modeling Nanoantennas Integral equations Hydrodynamics Mathematical models Characteristic mode analysis Numerical models

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A Comparison Diagnosis Algorithm for Conditional Fault Local Diagnosis of Multiprocessor Systems 25th

A Comparison Diagnosis Algorithm for Conditional Fault Loca...

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25th International computer Symposium on New Trends in computer Technologies and Applications, ICS 2022

作者： Lv, Yali Lin, Cheng-Kuan Hsu, D. Frank Fan, Jianxi School of Information Technology Henan University of Chinese Medicine Zhengzhou China Department of Computer Science National Yang Ming Chiao Tung University Hsinchu Taiwan Undergraduate Degree Program of Systems Engineering and Technology National Yang Ming Chiao Tung University Hsinchu Taiwan Computer Science and Information Engineering Chung Cheng Institute of Technology NDU Taoyuan City Taiwan Department of Computer and Information Science Fordham University New York United States School of Computer Science and Technology Soochow University Suzhou China

ISBN: (纸本)9789811995811

An efficient diagnosis is very important for a multiprocessor system. In this paper, we present a (α, β) -trees combination S(u, X, α, β) and give some conclusions about the local diagnosis. Based on the (α, β) -trees combination, we give a conditional fault local diagnosis algorithm to identify the fault or fault-free status of each processor correctly under the MM ∗ model when the number of faulty nodes does not exceed α+ 2 β- 3 and every node has at least one fault-free neighboring node. According to our results, a connected network with a (α, β) -trees combination S(u, X, α, β) for a node u is conditionally locally (α+ 2 β- 3 ) -diagnosable at node u and the time complexity of our algorithm to diagnose u is O(α2β+ αβ2). As an application, we show that our algorithm can identify all the faulty nodes of n-dimensional star graph Sn if the faulty node number does not exceed 3 n- 8. Compared with existing algorithms, our algorithm allows more faulty node in a multiprocessor system. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Computational complexity

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Exploring the Impact of Table-to-Text Methods on Augmenting LLM-based Question Answering with Domain Hybrid Data

arXiv

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arXiv 2024年

作者： Min, Dehai Hu, Nan Jin, Rihui Lin, Nuo Chen, Jiaoyan Chen, Yongrui Li, Yu Qi, Guilin Li, Yun Li, Nijun Wang, Qianren School of Computer Science and Engineering Southeast University China Department of Computer Science The University of Manchester United Kingdom Advanced Cognitive AI Lab Huawei Technologies China Key Laboratory of New Generation Artificial Intelligence Technology Southeast University Ministry of Education China

Augmenting Large Language Models (LLMs) for Question Answering (QA) with domain specific data has attracted wide attention. However, domain data often exists in a hybrid format, including text and semi-structured tables, posing challenges for the seamless integration of information. Table-to-Text Generation is a promising solution by facilitating the transformation of hybrid data into a uniformly text-formatted corpus. Although this technique has been widely studied by the NLP community, there is currently no comparative analysis on how corpora generated by different table-to-text methods affect the performance of QA systems. In this paper, we address this research gap in two steps. First, we innovatively integrate table-to-text generation into the framework of enhancing LLM-based QA systems with domain hybrid data. Then, we utilize this framework in real-world industrial data to conduct extensive experiments on two types of QA systems (DSFT and RAG frameworks) with four representative methods: Markdown format, Template serialization, TPLM-based method, and LLM-based method. Based on the experimental results, we draw some empirical findings and explore the underlying reasons behind the success of some methods. We hope the findings of this work will provide a valuable reference for the academic and industrial communities in developing robust QA systems. Copyright © 2024, The Authors. All rights reserved.

关键词： Metadata

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MULTI-RESOLUTION LOCATION-BASED TRAINING FOR MULTI-CHANNEL CONTINUOUS SPEECH SEPARATION

arXiv

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arXiv 2023年

作者： Taherian, Hassan Wang, DeLiang Department of Computer Science and Engineering The Ohio State University United States Center for Cognitive and Brain Sciences The Ohio State University United States

The performance of automatic speech recognition (ASR) systems severely degrades when multi-talker speech overlap occurs. In meeting environments, speech separation is typically performed to improve the robustness of ASR systems. Recently, location-based training (LBT) was proposed as a new training criterion for multi-channel talker-independent speaker separation. Assuming fixed array geometry, LBT outperforms widely-used permutation-invariant training in fully overlapped utterances and matched reverberant conditions. This paper extends LBT to conversational multi-channel speaker separation. We introduce multi-resolution LBT to estimate the complex spectrograms from low to high time and frequency resolutions. With multi-resolution LBT, convolutional kernels are assigned consistently based on speaker locations in physical space. Evaluation results show that multi-resolution LBT consistently outperforms other competitive methods on the recorded LibriCSS corpus. Copyright © 2023, The Authors. All rights reserved.

关键词： Location

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Reconfigurable Hardware Accelerator of Morphological Image Processor

Reconfigurable Hardware Accelerator of Morphological Image P...

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Electronic Communications, Internet of Things and Big Data (ICEIB), International Conference on

作者： Ming-Yi Lin Sheng-Hsien Hsieh Ching-Han Chen Department of Computer Science and Engineering Yuan Ze University Taoyuan Taiwan Bachelor's Program in Artificial Intelligence and Mechatronics National Pingtung University of Science and Technology Pingtung Taiwan Department of Computer Science and Information Engineering National Central University Taoyuan Taiwan

Researchers emphasize the importance of hardware accelerators for mathematical morphology. If there are any issues, the hardware architecture may need to be redesigned. Thus, we propose a novel, reconfigurable hardware architecture with pipeline techniques for acceleration. With the order control register, there is no need to modify the architecture even if different results are expected. Furthermore, the hardware architecture caters to specific purposes instead of requiring a purpose-built hardware design.

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Lightweight Pedestrian Detection through Guided Filtering and Deep Learning 10

Lightweight Pedestrian Detection through Guided Filtering an...

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10th IEEE Global Conference on Consumer Electronics, GCCE 2021

作者： Muchtar, Kahlil Saddami, Khairun Bintang, Akhyar Cenggoro, Tjeng Wawan Pardamean, Bens Lin, Chih-Yang Ernita, Tia Universitas Syiah Kuala Department of Electrical And Computer Engineering Aceh Indonesia Universitas Syiah Kuala Department of Electrical And Computer Engineering Aceh Indonesia Bina Nusantara University School of Computer Science Bina Nusantara University Bioinformatics And Data Science Research Center Computer Science Department Jakarta Indonesia Bina Nusantara University BINUS Graduate Program-Master of Computer Science Program Bina Nusantara University Bioinformatics And Data Science Research Center Computer Science Department Jakarta Indonesia Yuan-Ze University Department of Electrical And Engineering Taoyuan Taiwan

ISBN: (纸本)9781665436762

In this paper, we propose a novel approach to locate and detect moving pedestrians in a video. Our proposed method first locates the region of interest (ROI) using a background subtraction algorithm based on guided filtering. This novel background subtraction algorithm allows our method to also filter unexpected noises at the same time, which could benefit the performance of our proposed method. Subsequently, the pedestrians are detected using YOLOv3 within the provided ROI. Our experiments showed that the proposed method has a competitive performance in the CDNET2014 dataset with a fast-processing time. © 2021 IEEE.

关键词： Convolutional neural networks

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An Improved Particle Swarm Approach for Energy-Aware Location-Aided Routing in Mobile Ad-Hoc Network

An Improved Particle Swarm Approach for Energy-Aware Locatio...

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International Conference on Contemporary Computing and Informatics (IC3I)

作者： Sandeep Kumar Khemraj Sharma P. M. Ashok Kumar Arpit Jain Sukesh Kumar Bhagat Pranita Singh Tula’s institute Dehradun U.K India Department of Business Administration Doctoral Program in Management Sciences Nanhua University Dalin Chiayi R.O.C Department of Computer Science Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram AP India Department of Computer Science & Engineering Uttaranchal University Dehradun Uttarakhand India Department of Computer Science and Engineering Roorkee Institute of Technology Roorkee Uttarakhand India

ISBN: (数字)9798350350067

ISBN: (纸本)9798350350074

A network with no infrastructure, multiple hops, and dispersed nodes called a MANET. Nodes can communicate directly or through intermediaries without the need for permanent infrastructure. In dynamic networks like MANETs, routing procedures enhance the overall appearance of the network by ensuring Quality of Service (QoS). A routing protocol may use a composite routing measure to determine the best path for transferring data. Optimal location-based routing for MANETs based on energy-awareness is presented in this paper. Optimal routes are selected using this fast algorithm. Particle swarm optimization (PSO) is used instead of location-aided routing to select the normal data transmission route. Last but not least, the network is tested by simulating its packet delivery ratio, its energy level, its delay, and its overhead.

关键词： Scalability Transportation Quality of service Routing Particle measurements Routing protocols Real-time systems Delays Security Particle swarm optimization

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Normality Addition via Normality Detection in Industrial Image Anomaly Detection Models

arXiv

引用

arXiv 2024年

作者： Yi, Jihun Jung, Dahuin Yoon, Sungroh Department of Electrical and Computer Engineering Seoul National University Seoul Korea Republic of School of Computer Science and Engineering Soongsil University Seoul Korea Republic of Department of Electrical and Computer Engineering and Interdisciplinary Program in AI Seoul National University Seoul Korea Republic of

The task of image anomaly detection (IAD) aims to identify deviations from normality in image data. These anomalies are patterns that deviate significantly from what the IAD model has learned from the data during training. However, in real-world scenarios, the criteria for what constitutes normality often change, necessitating the reclassification of previously anomalous instances as normal. To address this challenge, we propose a new scenario termed "normality addition," involving the post-training adjustment of decision boundaries to incorporate new normalities. To address this challenge, we propose a method called Normality Addition via Normality Detection (NAND), leveraging a vision-language model. NAND performs normality detection which detect patterns related to the intended normality within images based on textual descriptions. We then modify the results of a pre-trained IAD model to implement this normality addition. Using the benchmark dataset in IAD, MVTec AD, we establish an evaluation protocol for the normality addition task and empirically demonstrate the effectiveness of the NAND method. Copyright © 2024, The Authors. All rights reserved.

关键词： Visual languages

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