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Semantic Template-based Convolutional Neural Network for Text Classification

ACM Transactions on Asian and Low-Resource Language information Processing 2023年第11期22卷 1-21页

作者： Chang, Yung-Chun Ng, Siu Hin Chen, Jung-Peng Liang, Yu-Chi Hsu, Wen-Lian Graduate Institute of Data Science Taipei Medical University Taipei Taiwan Clinical Big Data Research Center Taipei Medical University Hospital Taipei Taiwan Snhcc Tigp Academia Sinica National Cheng Chi University Taipei Taiwan Institute of Information Systems and Applications National Tsing Hua University Hsinchu Taiwan Department of Computer Science and Information Engineering College of Information and Electrical Engineering Asia University Taichung Taiwan Pervasive Ai Research Labs Ministry of Science and Technology Hsinchu City Taiwan

We propose a semantic template-based distributed representation for the convolutional neural network called Semantic Template-based Convolutional Neural Network (STCNN) for text categorization that imitates the perceptual behavior of human comprehension. STCNN is a highly automatic approach that learns semantic templates that characterize a domain from raw text and recognizes categories of documents using a semantic-infused convolutional neural network that allows a template to be partially matched through a statistical scoring system. Our experiment results show that STCNN effectively classifies documents in about 140,000 Chinese news articles into predefined categories by capturing the most prominent and expressive patterns and achieves the best performance among all compared methods for Chinese topic classification. Finally, the same knowledge can be directly used to perform a semantic analysis task. © 2023 held by the owner/author(s). Publication rights licensed to ACM.

关键词： Semantics

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Planar Wide Mesh Scanning using Multi-Probe systems 45

Planar Wide Mesh Scanning using Multi-Probe Systems

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45th Annual Meeting and Symposium of the Antenna Measurement Techniques Association, AMTA 2023

作者： Varela, Fernando Rodriguez Castaner, Manuel Sierra Saccardi, Francesco Scialacqua, Lucia Foged, Lars Universidad Rey Juan Carlos de Madrid Microwave Engineering and Radiocommunication Systems Group Spain Universidad Politecnica de Madrid Information Processing and Telecommunications Center Spain Microwave Vision Group Italy

ISBN: (纸本)9781736235157

The reduction of acquisition time in planar near field systems is a high interest topic when active arrays or multi beam antennas are measured. Different solutions have been provided in the last years: multi-probe measurements systems and the Planar Wide Mesh (PWM) methodology, which implements a non redundant sampling scheme that reduces the number of samples required for the far-field transformation, are two of the most well known techniques. This paper proposes the combination of both approaches to derive a multi-probe PWM grid which reduces the measurement times to the minimum. The method is based on treating the near-field to far-field transformation as an inverse source problem. The multi probe PWM is designed with a global optimization process which finds the best measurement locations of the probe array that guarantee a numerically stable inversion of the problem. A simulated measurement example with the VAST12 antenna is presented where the total number of samples is reduced by a factor of 100 using a 4×4 probe array. © 2023 AMTA.

关键词： Global optimization

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Urinary Bladder Monitoring with a Wearable Device Based on Bioimpedance Measurements and Machine Learning

Urinary Bladder Monitoring with a Wearable Device Based on B...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Fechner, Pascal Gros, Anika Lockl, Jannik Roglinger, Maximilian Tscheuschner, Niklas University of Bayreuth Bayreuth Germany University College London London United Kingdom Anhalt University of Applied Sciences Kothen Germany InContAlert GmbH Bayreuth Germany Branch Business and Information Systems Engineering of the Fraunhofer Fit Bayreuth Germany Fim Research Center for Information Management Bayreuth Germany

ISBN: (纸本)9798350386226

Neurogenic lower urinary tract dysfunction (NLUTD) can lead to an inability to recognize the need to empty the bladder. To the best of our knowledge, there is currently no established technological solution to assist patients. Prior research has demonstrated the potential of bioimpedance (BI) measurements combined with machine learning (ML) for the non-invasive monitoring of bladder filling. However, research on the processing of BI measurements under real-world conditions is scarce. In this paper, we built an ML-based prototype of a wearable BI device to validate and build on the results of existing work. We contribute to the body of knowledge by presenting an ML approach to leveraging BI measurements collected by a 16-electrode wearable device for bladder monitoring under real-world conditions. We validated our prototype with in-vivo experiments and evaluated its performance on a real-world dataset. The presented prototype employs a deep hybrid learning model based on convolutional and recurrent neural network architectures, which reaches a mean absolute error of 87.9 ml. In contrast to the current gold standard of time-based voiding, our prototype marks an important step toward a technological solution for NLUTD patients that is demand-driven and suitable for everyday use. © 2024 IEEE.

关键词： Recurrent neural networks

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Rolling the Dice – Rethinking the RAMI 4.0 Perspectives

Rolling the Dice – Rethinking the RAMI 4.0 Perspectives

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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Kristof Meixner David Hoffmann Sarah Riedmann Paula Hünecke Christoph Binder Christian Doppler Laboratory SQI Inst. of Information Systems Engineering TU Wien Institute of Ergonomics Manufacturing Systems and Automation Otto-von-Guericke U. Germany Josef Ressel Center for Dependable System-of-Systems Engineering Austria

ISBN: (数字)9798350361230

ISBN: (纸本)9798350361247

As developing current or future industrial systems becomes increasingly complex, new methods for understandably structuring those systems need to arise. The Reference Architectural Model Industrie 4.0 (RAMI 4.0) provides a framework for describing intermingled industrial applications in the context of Cyber-Physical Production systems (CPPSs). However, although RAMI 4.0 has been standardized for almost a decade, it still lacks actual industrial applications. Recent use cases have shown that the three-dimensional layout might be oversimplified for describing system architectures. Specifically, problems with the so-called live-cycle axis, which has shown significant shortcomings in capturing the dynamics of industrial processes, need to be tackled. This paper provides an analysis of RAMI 4.0 and an assessment of shortcomings that hinder its applicability. It presents alternative approaches that address these limitations by proposing modifications or replacements of parts of RAMI 4.0. Based on the paper's insights, we provide the research agenda for engineering future manufacturing systems, considering it a base for follow-up projects to ensure industrial readiness.

关键词： Industries Industrial control Layout systems architecture Collaboration Rigidity Complexity theory Standards Manufacturing automation Context modeling

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Digital Twin Agent for Super-Aged Society

Digital Twin Agent for Super-Aged Society

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2022 IEEE International Conference on Consumer Electronics, ICCE 2022

作者： Kobayashi, Toru Fukae, Kazuki Imai, Tetsuo Arai, Kenichi Graduate School of Engineering Nagasaki University Division of Electrical Engineering and Computer Science Nagasaki Japan Hiroshima City University Graduate School of Information Sciences Department of Intelligent Systems Hiroshima Japan

ISBN: (纸本)9781665441544

We propose a digital twin agent that constructs elderly digital twins by digitally transforming daily life of the elderly. We developed the digital twin agent as an avatar run on a smartwatch. The digital twin agent provides cooperation support functions with the society to the elderly. Those support function histories will be integrated with the digital twin. The digital twin agent can also monitor indoor daily life activities using distributed small sensors inside home. Then, those monitoring results will be integrated with the same digital twin. We confirmed that the digital twin agent could provide cooperation support functions with the society through evaluation experiments in Nagasaki city in Japan. We also confirmed that the digital twin agent could construct the digital twin based on those support function histories and offer mental health support functions using the constructed digital twin. © 2022 IEEE.

关键词： Resource Description Framework (RDF)

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Performance Recovery in Event-Triggered State Feedback Control

Performance Recovery in Event-Triggered State Feedback Contr...

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2023 IEEE Conference on Control Technology and Applications, CCTA 2023

作者： Kurtoglu, Deniz Yucelen, Tansel Tran, Dzung Casbeer, David Garcia, Eloy University of South Florida Laboratory for Autonomy Control Information and Systems Graduate Student of the Department of Mechanical Engineering TampaFL33620 United States University of South Florida Laboratory for Autonomy Control Information and Systems Department of Mechanical Engineering TampaFL33620 United States Wright-Patterson Air Force Base Air Force Research Laboratory Control Science Center OH45433 United States

ISBN: (纸本)9798350335446

The idea behind event-triggered control theory is to aperiodically schedule control data transmissions between an embedded processor and a physical system based on event rules. While this theory can effectively reduce control data transmissions, the resulting closed-loop system performance can significantly deviate from its ideal (i.e., non-event-triggered) closed-loop system performance. Furthermore, the selection of the parameters of the event rules can be a challenge in obtaining a satisfactory closed-loop system performance that stays close to its ideal one. Motivated by this standpoint, the contribution of this paper is to make the first attempt in rigorously addressing this problem, where we propose a corrective signal for recovering the ideal closed-loop system performance in event-triggered control. The key feature of the proposed corrective signal is that the closed-loop system performance approaches its ideal one in a quantifiable manner as the gain of this corrective signal is increased. System-theoretical analysis of the proposed method is presented and illustrative numerical examples are also given to demonstrate the efficacy of our contribution. © 2023 IEEE.

关键词： Closed loop systems

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Towards Additive Manufacturing Based Packaging of Mm-Wave Antenna Arrays and Beamformer ICs

Towards Additive Manufacturing Based Packaging of Mm-Wave An...

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IEEE Annual Conference on Wireless and Microwave Technology (WAMICON)

作者： Ruoke Liu Gokhan Mumcu Jing Wang Department of Electrical Engineering Center for Wireless and Microwave Information Systems University of South Florida Tampa FL USA

Laser enhanced direct print additive manufacturing (LE-DPAM) technology has recently been demonstrated to achieve success in packaging of antennas with phase shifters to realize passive phased antenna arrays (PAAs). Utilizing LE-DPAM for PAAs operating in mm-wave bands brings out new challenges that need to be addressed. These challenges are associated with smaller antenna and feature sizes needed for mm-wave band operation, necessity of active circuits for amplification, and number of pads, pad size and pad locations of mm-wave beamformer IC packages. This paper presents our initial progress in scaling LE-DPAM based packaging of PAAs into the mm-wave band operation through consideration and demonstration of discrete components (i.e. antenna array elements and beamformer ICs) that form the PAA structure. Specifically, a stand-alone, passive, 2×2 LE-DPAM based 26 GHz antenna subarray is investigated for its performance. In addition, a 24.5 GHz – 27 GHz beamformer IC is packaged in a stand-alone test article using LE-DPAM and investigated for its mm-wave performance and thermal aspects.

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Construction and application of high-quality genome-scale metabolic model of Zymomonas mobilis to guide rational design of microbial cell factories

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Synthetic and systems Biotechnology 2023年第3期8卷 498-508页

作者： Yalun Wu Qianqian Yuan Yongfu Yang Defei Liu Shihui Yang Hongwu Ma State Key Laboratory of Biocatalysis and Enzyme Engineering School of Life SciencesHubei UniversityWuhan430062HubeiChina Biodesign Center Key Laboratory of Systems Microbial BiotechnologyTianjin Institute of Industrial BiotechnologyChinese Academy of SciencesTianjin300308China Hubei Key Laboratory of Applied Mathematics Faculty of Mathematics and StatisticsHubei UniversityWuhan430062HubeiChina Artificial Intelligence and Knowledge Engineering Lab School of Computer Science and Information EngineeringHubei UniversityWuhan430062HubeiChina

High-quality genome-scale metabolic models(GEMs)could play critical roles on rational design of microbial cell factories in the classical Design-Build-Test-Learn cycle of synthetic biology *** of the constant establishment and update of GEMs for model microorganisms such as Escherichia coli and Saccharomyces cerevisiae,high-quality GEMs for non-model industrial microorganisms are still *** mobilis *** ZM4 is a non-model ethanologenic microorganism with many excellent industrial characteristics that has been developing as microbial cell factories for biochemical *** five GEMs of *** have been constructed,these models are either generating ATP incorrectly,or lacking information of plasmid genes,or not providing standard format *** this study,a high-quality GEM iZM516 of *** ZM4 was *** information from the improved genome annotation,literature,datasets of Biolog Phenotype Microarray studies,and recently updated Gene-Protein-Reaction information was combined for the curation of ***,516 genes,1389 reactions,1437 metabolites,and 3 cell compartments are included in iZM516,which also had the highest MEMOTE score of 91%among all published GEMs of *** growth was then predicted by iZM516,which had 79.4%agreement with the experimental results of the substrate *** addition,the potential endogenous succinate synthesis pathway of *** ZM4 was proposed through simulation and analysis using ***,metabolic engineering strategies to produce succinate and 1,4-butanediol(1,4-BDO)were designed and then simulated under anaerobic condition using *** results indicated that 1.68 mol/mol succinate and 1.07 mol/mol 1,4-BDO can be achieved through combinational metabolic engineering strategies,which was comparable to that of the model species *** study thus not only established a high-quality GEM iZM516 to help understand and design microbial cell fac

关键词： Genome-scale metabolic models(GEMSs) Non-model industrial microorganism Zymomonas mobilis Biolog phenotype microarray Succinate 1,4-Butanediol

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Incremental Learning with Pseudo Labels for Enhanced Glomeruli Segmentation Using SAM

Incremental Learning with Pseudo Labels for Enhanced Glomeru...

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2024 IEEE International Conference on E-Health Networking, Application and Services, HealthCom 2024

作者： Liu, Xinkai Peng, Boyuan Zhu, Xin Iwasaki, Tsuyoshi Sato, Atsuya Kazama, Junichiro James Huang, Jie Graduate Department of Computer Science and Engineering The University of Aizu Fukushima Aizu-Wakamatsu Japan Department of AI Technology Development M&D Data Science Center Institute of Science Tokyo Tokyo Japan Department of Nephrology and Hypertension Fukushima Medical University Fukushima Japan Graduate Department of Computer Science and Engineering Division of Information Systems The University of Aizu Fukushima Aizu-Wakamatsu Japan

ISBN: (纸本)9798350350548

The advent of the Segment Anything Model (SAM) marks a significant milestone in deep learning semantic segmentation tasks. In this study, an incremental learning model based on pseudo labels is proposed. The model generates bounding box prompts for SAM, enhancing the accuracy of glomeruli segmentation in renal pathology images. The model uses DenseNet-121 along with contrastive learning to enable self-supervised pre-training using mouse glomeruli images. Transfer learning is then conducted using labeled human renal pathology images to develop a binary classification model for glomeruli. Unlabeled images of human renal pathology are subsequently introduced for incremental learning. Class activation maps (CAMs) generated by the incremental learning model are post-processed to extract bounding rectangles for connected regions. These rectangles are then used as prompts for SAM segmentation. The proposed approach resulted in an average Dice similarity coefficient (DSC) of 0.825 in the glomeruli segmentation task. This result demonstrates the effectiveness of the incremental learning model and post-processing algorithms in improving SAM’s segmentation accuracy for renal pathology. © 2024 IEEE.

关键词： Contrastive Learning

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Sensing Small Uncrewed Aerial Vehicles with Distributed Radars for Advanced Air Mobility Surveillance

Sensing Small Uncrewed Aerial Vehicles with Distributed Rada...

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AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Vitiello, Federica Causa, Flavia Opromolla, Roberto Fasano, Giancarmine Dolph, Chester Ferrante, Todd Lombaerts, Thomas Ippolito, Corey A. Department of Industrial Engineering University of Naples "Federico II" Piazzale Tecchio 80 Naples80125 Italy Aeronautics Systems Engineering NASA Langley Research Center 1 Nasa Dr HamptonVA23666 United States Analytical Mechanics Associates Inc. NASA Langley Research Center 1 Nasa Dr HamptonVA23666 United States KBR Wyle Services NASA Ames Research Center Moffett FieldCA94035 United States Intelligent Systems Division NASA Ames Research Center Moffett FieldCA94035 United States

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

In the context of Advanced and Urban Air Mobility major attention is being reserved to the development of sensing strategies for small Uncrewed Aerial Vehicles (sUAVs) to enable their safe operations in and around urban areas. Such strategies should rely on non-cooperative distributed sensors to strengthen the surveillance solution towards the unreliability of Global Navigation Satellite System (GNSS) positioning information, which is typical for low-altitude-flying platforms in urban regions, and increase the monitored airspace volume. To this aim, this paper proposes a fusion solution for a network of distributed ground-based radars, which can be exploited to not only increase the coverage over large airspace volumes but also improve the overall detectability and traceability of sUAVs by leveraging on multiple views over the same area. The solution exploits a centralized fusion scheme in which measurements collected by each radar are shared with a Fusion center where Kalman Filtering is exploited to build a unique, fused track. Tests conducted on experimental data collected using two sUAVs as flying targets and three distributed radars showed that the proposed solution can produce an increase in coverage from about 20 % (single radar configuration) to about 80 % of the targets’ flight path, as well as a finer accuracy yielding meter and meter-per-second root mean square error values on position and velocity components. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Air mobility

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