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arXiv 2022年

作者： Chen, Weibin Sharifrazi, Danial Liang, Guoxi Band, Shahab S. Chau, Kwok Wing Mosavi, Amir College of Computer Science and Artificial Intelligence Wenzhou University Zhejiang Wenzhou325035 China Department of Computer Engineering Shiraz Branch Islamic Azad University Shiraz Iran Department of Artificial Intelligence Wenzhou Polytechnic Wenzhou325035 China Future Technology Research Center College of Future National Yunlin University of Science and Technology Yunlin County Taiwan Department of Civil and Environmental Engineering Hong Kong Polytechnic University Hong Kong John von Neumann Faculty of Informatics Obuda University Budapest Hungary Institute of Information Engineering Automation and Mathematics Slovak University of Technology Bratislava Slovakia

Streamlined weirs, as a nature-inspired type of weirs, has gained tremendous attention among hydraulic engineers mainly due to their well-known performance with high discharge coefficient. Computational fluid dynamic (CDF) is considered as a robust tool to predict discharge coefficient. To bypass the computational cost of CFD-based assessment, the present study proposes data-driven modelling techniques, as an alternative to CFD simulation, to predict discharge coefficient based on an experimental dataset. To this end, after splitting the dataset by k-fold cross-validation technique, the performance assessment of classical and hybrid machine-deep learning (ML-DL) algorithms is undertaken. Amongst ML techniques, linear regression (LR), random forest (RF), support vector machine (SVM), k-nearest neighbours (KNN), and decision tree (DT) algorithms are studied . In the context of DL, long short-term memory (LSTM), convolutional neural network (CNN), gated recurrent unit (GRU) and their hybrid forms such as LSTM-GRU, CNN-LSTM and CNN-GRU techniques are compared by different error metrics. It is found that the proposed three-layer hierarchical DL algorithm consisting of a convolutional layer coupled with two subsequent GRU levels, which is also hybridized by LR method (i.e., LR-CGRU), leads to lower error metrics. This paper paves the way for data-driven modelling of streamlined *** Codes 68T05 © 2022, CC BY.

关键词： Deep neural networks

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A Comprehensive Survey with Quantitative Comparison of Image Analysis Methods for Microorganism Biovolume Measurements

arXiv

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arXiv 2022年

作者： Zhang, Jiawei Li, Chen Rahaman, Md Mamunur Yao, Yudong Ma, Pingli Zhang, Jinghua Zhao, Xin Jiang, Tao Grzegorzek, Marcin Microscopic Image and Medical Image Analysis Group College of Medicine and Biological Information Engineering Northeastern University Shenyang110169 China Department of Electrical and Computer Engineering Stevens Institute of Technology HobokenNJ07030 United States School of Resources and Civil Engineering Northeastern University Shenyang110004 China School of Control Engineering Chengdu University of Information Technology Chengdu610225 China Institute of Medical Informatics University of Luebeck Luebeck23538 Germany School of Computer Science and Engineering University of New South Wales SydneyNSW2052 Australia

With the acceleration of urbanization and living standards, microorganisms play an increasingly important role in industrial production, bio-technique, and food safety testing. Microorganism biovolume measurements are one of the essential parts of microbial analysis. However, traditional manual measurement methods are time-consuming and challenging to measure the characteristics precisely. With the development of digital image processing techniques, the characteristics of the microbial population can be detected and quantified. The applications of the microorganism biovolume measurement method have developed since the 1980s. More than 62 articles are reviewed in this study, and the articles are grouped by digital image analysis methods with time. This study has high research significance and application value, which can be referred to as microbial researchers to comprehensively understand microorganism biovolume measurements using digital image analysis methods and potential applications. © 2022, CC0.

关键词： Microorganisms

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Node based Label Propagation for Bitcoin Transaction Pattern Identification Over Similar Community

Node based Label Propagation for Bitcoin Transaction Pattern...

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International Conference on Inventive Computation Technologies (ICICT)

作者： Manika Manwal Ahmad Murtaza Alvi Nagendra Kumar Turaga Amit Mittal Richard Rivera Sheshang Degadwala CSE Graphic Era Hill University Dehradun India CSE Graphic Era deemed to be University Dehradun India Department of Business Administration College of Finance Saudi Electronic University Riyadh Saudi Arabia Department of Management Studies Vignan's Foundation for Science Technology and Research (Deemed to be University) Department of Allied Science Graphic Era Hill University Bhimtal Department of Informatics and Computer Science Escuela Politecnica Nacional. Quito Ecuador Sigma Institute of Engineering Engineering Block Sigma Group of Institutes Bakrol Vadodara Gujarat

People have conducted decentralized transfer transactions through Bitcoin addresses ever since the Bitcoin system launched online, drastically improving the convenience of transactions. Simultaneously, peer-to-peer transaction logs have become a subject of study. However, it requires a significant amount of time and computing capacity to examine the entire network directly, and it is not conducive to observing the transaction mode within the entity. Consequently, it is possible to construct and analyses the transaction network based on the entity service community and further investigate entity behavior and Bitcoin entities within the service community. A central node-based label propagation algorithm is proposed by enhancing the conventional label propagation algorithm, which divides the Bitcoin entity transaction network into districts and analyses the core communities, including exchanges and mining pools. The transaction method is realistic and straightforward to comprehend. The enhanced label propagation algorithm can converge more quickly and reduce the randomness of the results of community division. The experimental results demonstrate that the internal transaction modalities of various services vary. The simplified display makes the Bitcoin transaction network more readable.

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Noisy Neonatal Chest Sound Separation for High-Quality Heart and Lung Sounds

arXiv

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arXiv 2022年

作者： Grooby, Ethan Sitaula, Chiranjibi Fattahi, Davood Sameni, Reza Tan, Kenneth Zhou, Lindsay King, Arrabella Ramanathan, Ashwin Malhotra, Atul Dumont, Guy A. Marzbanrad, Faezeh Department of Electrical and Computer Systems Engineering Monash University MelbourneVIC Australia Shiraz University Shiraz Iran Department of Biomedical Informatics Emory University AtlantaGA United States Monash Newborn Monash Children’s Hospital Department of Paediatrics Monash University Melbourne Australia Department of Electrical and Computer Engineering University British Columbia VancouverBC Canada BC Children’s Hospital Research Institute VancouverBC Canada

Stethoscope-recorded chest sounds provide the opportunity for remote cardio-respiratory health monitoring of neonates. However, reliable monitoring requires high-quality heart and lung sounds. This paper presents novel Non-negative Matrix Factorisation (NMF) and Non-negative Matrix Co-Factorisation (NMCF) methods for neonatal chest sound separation. To assess these methods and compare with existing single-source separation methods, an artificial mixture dataset was generated comprising of heart and lung and noise sounds. Signal-to-noise ratios were then calculated for these artificial mixtures. These methods were also tested on real-world noisy neonatal chest sounds and assessed based on vital sign estimation error and a signal quality score of 1-5 developed in our previous works. Additionally, the computational cost of all methods was assessed to determine the applicability for real-time processing. Overall, both the proposed NMF and NMCF methods outperform the next best existing method by 2.7 dB to 11.6 dB for the artificial dataset and 0.40 to 1.12 signal quality improvement for the real-world dataset. The median processing time for the sound separation of a 10 s recording was found to be 28.3 s for NMCF and 342 ms for NMF. Because of stable and robust performance, we believe that our proposed methods are useful to denoise neonatal heart and lung sound in a real-world environment. Codes for proposed and existing methods can be found at: https://github. com/egrooby-monash/Heart-and-Lung-Sound-Separation. Copyright © 2022, The Authors. All rights reserved.

关键词： Source separation

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Visual servo guided cyber-physical robotic assembly cell

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IFAC-PapersOnLine 2021年第1期54卷 595-600页

作者： Gábor Erdős Dániel Horváth Gergely Horváth Centre of Excellence in Production Informatics and Control Institute for Computer Science and Control Eötvös Loránd Research Network Budapest Hungary Department of Manufacturing Science and Engineering Budapest University of Technology and Economics Hungary Department of Software Technology and Methodology Eötvös Loránd University Hungary

Advanced robotic assembly systems are promising great benefits to the manufacturing sector, once the shortcomings of the current technologies are overcome. One of the biggest obstacles to introducing flexible robotic systems is the ability of robots to sense and perceive the semi-structured or unstructured environment. This paper presents a cyber-physical system based framework of a robotic assembly cell that is capable of recognizing resources of assembly processes, based on information from various visual sensors and updating and adapting the assembly plan in the digital twin of the robotic cell. Thus, calculates and executes feasible motion plans of the robots based on accurate digital information. The application of the framework is demonstrated in a physical assembly process.

关键词： Process Planning Intelligent Manufacturing Systems Intelligent Robot Services in Manufacturing

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Indexed Multiple Access with Reconfigurable Intelligent Surfaces: The Reflection Tuning Potential

arXiv

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arXiv 2023年

作者： Singh, Rohit Kaushik, Aryan Shin, Wonjae Alexandropoulos, George C. Toka, Mesut Renzo, Marco Di The Department of Electronics and Communication Engineering Dr. B. R. Ambedkar National Institute of Technology Jalandhar144027 India The School of Engineering and Informatics University of Sussex BrightonBN1 9RH United Kingdom The Department of Electrical and Computer Engineering Ajou University Suwon-si16499 Korea Republic of The Department of Electrical Engineering Princeton University PrincetonNJ08544 United States The Department of Informatics and Telecommunications National and Kapodistrian University of Athens Athens15784 Greece The Technology Innovation Institute Masdar City Abu Dhabi9639 United Arab Emirates Paris-Saclay University CNRS CentraleSupelec Laboratoire des Signaux et Systemes 3 Rue Joliot-Curie Gif-surYvette91192 France

Indexed modulation (IM) is an evolving technique that has become popular due to its ability of parallel data communication over distinct combinations of transmission entities. In this article, we first provide a comprehensive survey of IM-enabled multiple access (MA) techniques, emphasizing the shortcomings of existing non-indexed MA schemes. Theoretical comparisons are presented to show how the notion of indexing eliminates the limitations of non-indexed solutions. We also discuss the benefits that the utilization of a reconfigurable intelligent surface (RIS) can offer when deployed as an indexing entity. In particular, we propose an RIS-indexed multiple access (RIMA) transmission scheme that utilizes dynamic phase tuning to embed multi-user information over a single carrier. The performance of the proposed RIMA is assessed in light of simulation results that confirm its performance gains. The article further includes a list of relevant open technical issues and research directions. Copyright © 2023, The Authors. All rights reserved.

关键词： Transmissions

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Characterization of Indoor RIS-Assisted Channels at 304 GHz: Experimental Measurements, Challenges, and Future Directions

arXiv

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arXiv 2024年

作者： Alexandropoulos, George C. Jung, Bo Kum Gavriilidis, Panagiotis Matos, Sérgio Loeser, Lorenz H.W. Elesina, Varvara Clemente, Antonio D’Errico, Raffaele Pessoa, Luís M. Kürner, Thomas The Department of Informatics and Telecommunications National and Kapodistrian University of Athens Athens15784 Greece The Department of Electrical and Computer Engineering University of Illinois Chicago ChicagoIL60601 United States The Institute for Communications Technology Technische Universität Braunschweig Braunschweig38106 Germany Lisbon1649-026 Portugal CEA-Leti MINATEC Campus Grenoble38054 France Universite Grenoble Alpes France INESC TEC The Faculty of Engineering University of Porto Campus da FEUP Porto4200-465 Portugal

Reconfigurable Intelligent Surfaces (RISs) are expected to play a pivotal role in future indoor ultra high data rate wireless communications as well as highly accurate three-dimensional localization and sensing, mainly due to their capability to provide flexible, cost- and power-efficient coverage extension, even under blockage conditions. However, when considering beyond millimeter wave frequencies where there exists GHz-level available bandwidth, realistic models of indoor RIS-parameterized channels verified by field-trial measurements are unavailable. In this article, we first present and characterize three RIS prototypes with 100×100 unit cells of half-wavelength inter-cell spacing, which were optimized to offer a specific non-specular reflection with 1-, 2-, and 3-bit phase quantization at 304 GHz. The designed static RISs were considered in an indoor channel measurement campaign carried out with a 304 GHz channel sounder. Channel measurements for two setups, one focusing on the transmitter-RIS-receiver path gain and the other on the angular spread of multipath components, are presented and compared with both state-of-the-art theoretical models as well as full-wave simulation results. The article is concluded with a list of challenges and research directions for RIS design and modeling of RIS-parameterized channels at THz frequencies. © 2024, CC BY-NC-ND.

关键词： Velocity measurement

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A Fully Programmable On-Chip Planar Waveguide for Machine Learning

A Fully Programmable On-Chip Planar Waveguide for Machine Le...

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Conference on Lasers and Electro-Optics (CLEO)

作者： Martin M. Stein Tatsuhiro Onodera Benjamin A. Ash Mandar M. Sohoni Melissa Bosch Ryotatsu Yanagimoto Marc Jankowski Timothy P. McKenna Tianyu Wang Gennady Shvets Maxim R. Shcherbakov Logan G. Wright Peter L. McMahon School of Applied and Engineering Physics Cornell University Ithaca NY USA NTT Physics and Informatics Laboratories NTT Research Inc. Sunnyvale CA USA E. L. Ginzton Laboratory Stanford University Stanford CA USA Department of Electrical Engineering and Computer Science UC Irvine Irvine CA USA Department of Applied Physics Yale University New Haven CT USA Kavli Institute at Cornell for Nanoscale Science Cornell University Ithaca NY USA

We introduce a device containing a planar waveguide whose spatial refractive index profile $n(x, z)$ can be programmed in real time. We demonstrate use this device as an optical neural network.

ISBN: (纸本)9798350369311

We introduce a device containing a planar waveguide whose spatial refractive index profile $n(x, z)$ can be programmed in real time. We demonstrate use this device as an optical neural network.

关键词： Optical planar waveguides Refractive index Waveguide lasers Optical fiber networks Optical variables control Real-time systems Planar waveguides System-on-chip Optical refraction Optical devices

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Learning Inter-Lingual Document Representations via Concept Compression 22nd

Learning Inter-Lingual Document Representations via Concept ...

引用

22nd International Conference on Intelligent Data engineering and Automated Learning, IDEAL 2021

作者： Lenz, Marc Tashu, Tsegaye Misikir Horváth, Tomáš Faculty of Informatics Department of Data Science and Engineering Telekom Innovation Laboratories ELTE - Eötvös Loránd University Pázmány Péter Sétány Budapest1117 Hungary College of Informatics Wollo University Kombolcha Institute of Technology Kombolcha208 Ethiopia Faculty of Science Institute of Computer Science Pavol Jozef Šafárik University Jesenná 5 Košice040 01 Slovakia

ISBN: (纸本)9783030916077

In this work, we proposed a novel approach to derive inter-lingual document representations. The introduced methods aim to enhance the quality of content-based Multilingual Document Recommendation and information retrieval Systems. The main idea centers around creating inter-lingual representations by using mappings to align monolingual representation spaces. According to the experimental results carried out on JRC-Acquis and EU bookshop multilingual corpora, the proposed concept compression approach has outperformed the traditional cross-lingual retrieval and recommendations methods. © 2021, Springer Nature Switzerland AG.

关键词： Information retrieval systems

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A deep learning approach to Lung Nodule Growth Prediction using CT image combined with Demographic and image features 23

A deep learning approach to Lung Nodule Growth Prediction us...

引用

7th International Conference on Medical and Health informatics, ICMHI 2023

作者： Li, Ai-Hsien Adams Nguyen, Duc-Khanh Lai, Yen-Jun Chien, Ting-Ying Chiu, Yen-Ling Chan, Chien-Lung Yang, Pan-Chyr Division of Cardiology Far Eastern Memorial Hospital Taipei220 Taiwan Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan City Taiwan Department of Information Management Yuan Ze University Taoyuan320 Taiwan Department of Radiology Far Eastern Memorial Hospital Taipei220 Taiwan Department of Computer Science and Engineering Yuan Ze University Taoyuan City Taiwan Innovation Center for Big Data and Digital Convergence Yuan Ze University Taoyuan City Taiwan Graduate Institute of Medicine and Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan Taiwan Department of Medical Research Far Eastern Memorial Hospital Taipei Taiwan Innovation Center for Big Data and Digital Convergence Yuan Ze University Taoyuan320 Taiwan Institute of Biomedical Sciences Academia Sinica Taipei106 Taiwan Department of Internal Medicine College of Medicine National Taiwan University Taipei100 Taiwan Center of Genomic Medicine National Taiwan University Taipei100 Taiwan

ISBN: (纸本)9798400700712

Lung cancer remains a significant global public health concern, being the leading cause of cancer-related deaths worldwide. Despite recent medical advancements, the disease still has a high mortality rate, making early detection and treatment critical for improving patient outcomes. Accurate prediction of nodule growth is key to early lung cancer treatment, but current assessments offer unclear indications of future growth, leading physicians to recommend costly and anxiety-provoking follow-up appointments every 3 to 12 months. To address this need, this study develops an ensemble deep learning approach that combines demographic data with existing CT images to predict whether lung nodules will grow, potentially reducing unnecessary examinations and easing the burden on patients. Our study, conducted on 862 patients with 1004 nodules, produced promising preliminary results with Accuracy, Sensitivity, Precision, F1 Score, and AUC of 0.66, 0.66, 0.67, 0.66, and 0.71, respectively. The proposed method provides a promising support system to empower patients to make informed decisions about seeking medical attention and helps physicians facilitate early treatment regimens, leading to improved patient outcomes and potentially saving lives. © 2023 ACM.

关键词： Forecasting

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