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Substrate tuned reconstructed polymerization of naphthalocyanine on Ag(110)

Chinese Physics B 2022年第1期31卷 107-111页

作者： Qi Zheng Li Huang Deliang Bao Rongting Wu Yan Li Xiao Lin Shixuan Du Hong-Jun Gao Beijing National Center for Condensed Matter Physics and Institute of Physics Chinese Academy of SciencesBeijing 100190China School of Physical Sciences University of Chinese Academy of SciencesBeijing 100049China CAS Center for Excellence in Topological Quantum Computation University of Chinese Academy of SciencesBeijing 100190China Department of Physics and Astronomy and Department of Electrical Engineering and Computer Science Vanderbilt UniversityNashvilleTN 37235USA Songshan Lake Materials Laboratory Dongguan 523808China

The linkage structures between monomers make great influence on the properties of *** synthesis of some special linkage structures can be challenging,which is often overcome by employing special reaction ***,we build dihydropentalene linkage in poly-naphthalocyanine on Ag(110)*** tunneling microscopy(STM)and non-contact atomic force microscopy(nc-AFM)measurements confirm the dihydropentalene linkage structure and a possible formation path with reconstruction steps is *** controlled experiment on Ag(100)surface shows no dihydropentalene structures formed,which indicates the grooved substrate is necessary for the *** work provides insights into the surface restricted reactions that can yield special structures in organic polymers.

关键词： on-surface polymerization reconstruction scanning tunneling microscopy noncontact atomic force microscopy

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Temporally Consistent Referring Video Object Segmentation with Hybrid Memory

arXiv

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arXiv 2024年

作者： Miao, Bo Bennamoun, Mohammed Gao, Yongsheng Shah, Mubarak Mian, Ajmal The Department of Computer Science and Software Engineering The University of Western Australia Perth CrawleyWA6009 Australia The School of Engineering Griffith University BrisbaneQLD4111 Australia The Center for Research in Computer Vision University of Central Florida OrlandoFL32816 United States

Referring Video Object Segmentation (R-VOS) methods face challenges in maintaining consistent object segmentation due to temporal context variability and the presence of other visually similar objects. We propose an end-to-end R-VOS paradigm that explicitly models temporal instance consistency alongside the referring segmentation. Specifically, we introduce a novel hybrid memory that facilitates inter-frame collaboration for robust spatio-temporal matching and propagation. Features of frames with automatically generated high-quality reference masks are propagated to segment the remaining frames based on multi-granularity association to achieve temporally consistent R-VOS. Furthermore, we propose a new Mask Consistency Score (MCS) metric to evaluate the temporal consistency of video segmentation. Extensive experiments demonstrate that our approach enhances temporal consistency by a significant margin, leading to top-ranked performance on popular R-VOS benchmarks, i.e., Ref-YouTube-VOS (67.1%) and Ref-DAVIS17 (65.6%). The code is available at https://***/bo-miao/HTR. © 2024, CC BY.

关键词： Video analysis

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MTGA: Multi-View Temporal Granularity Aligned Aggregation for Event-Based Lip-Reading

arXiv

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arXiv 2024年

作者： Zhang, Wenhao Wang, Jun Luo, Yong Yu, Lei Yu, Wei He, Zheng Shen, Jialie School of Computer Science National Engineering Research Center for Multimedia Software Hubei Key Laboratory of Multimedia and Network Communication Engineering Wuhan University China School of Electronics and Information Wuhan University China Department of Computer Science City University of London United Kingdom

Lip-reading is to utilize the visual information of the speaker’s lip movements to recognize words and sentences. Existing event-based lip-reading solutions integrate different frame rate branches to learn spatio-temporal features of varying granularities. However, aggregating events into event frames inevitably leads to the loss of fine-grained temporal information within frames. To remedy this drawback, we propose a novel framework termed Multi-view Temporal Granularity aligned Aggregation (MTGA). Specifically, we first present a novel event representation method, namely time-segmented voxel graph list, where the most significant local voxels are temporally connected into a graph list. Then we design a spatio-temporal fusion module based on temporal granularity alignment, where the global spatial features extracted from event frames, together with the local relative spatial and temporal features contained in voxel graph list are effectively aligned and integrated. Finally, we design a temporal aggregation module that incorporates positional encoding, which enables the capture of local absolute spatial and global temporal information. Experiments demonstrate that our method outperforms both the event-based and video-based lip-reading counterparts. Copyright © 2024, The Authors. All rights reserved.

关键词： Feature extraction

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Deep Learning for Object Detection:A Survey

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computer Systems Science & engineering 2021年第8期38卷 165-182页

作者： Jun Wang Tingjuan Zhang Yong Cheng Najla Al-Nabhan Science and Technology Industry Department Nanjing University of Information Science&Technology210044China School of Computer&Software Jiangsu Engineering Center of Network MonitoringNanjing University of Information Science&Technology210044China Department Computer Science King Saud UniversityRiyadhKSA

Object detection is one of the most important and challenging branches of computer vision,which has been widely applied in people s life,such as monitoring security,autonomous driving and so on,with the purpose of locating instances of semantic objects of a certain *** the rapid development of deep learning algorithms for detection tasks,the performance of object detectors has been greatly *** order to understand the main development status of target detection,a comprehensive literature review of target detection and an overall discussion of the works closely related to it are presented in this *** paper various object detection methods,including one-stage and two-stage detectors,are systematically summarized,and the datasets and evaluation criteria used in object detection are *** addition,the development of object detection technology is ***,based on the understanding of the current development of target detection,we discuss the main research directions in the future.

关键词： Object detection convolutional neural network computer vision

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SpaceCube GHOST: A Resilient Processor for Low-Power, High-Reliability Space Computing

SpaceCube GHOST: A Resilient Processor for Low-Power, High-R...

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IEEE Conference on Aerospace

作者： Noah Perryman Nicholas Franconi Gary Crum Christopher Wilson Alan D. George Department of Electrical and Computer Engineering NSF Center for Space High-Performance and Resilient Computing (SHREC) University of Pittsburgh Pittsburgh PA Science Data Processing Branch Code 587 Software Engineering Division NASA Goddard Space Flight Center Greenbelt MD

There is a direct need for high-visibility NASA missions that provide significant scientific impact or have a high mission class using completely radiation-hardened (rad-hard) electronics solutions, to enable artificial intelligence (AI) applications in harsh environments despite severe size, weight, and power (SWaP) constraints. For these missions, where current state-of-the-art solutions are too power-demanding or are incapable of surviving the intended radiation environment, an alternative rad-hard processing architecture that can leverage the control-flow capabilities of scalar processors while also incorporating the hardware-acceleration capabilities of an FPGA is of significant value. Therefore, in this research, we propose a miniaturized (3.5 in. × 3.5 in. form factor) processor card featuring the GR740 quad-core rad-hard processor and the CertusPro-NX-RT radiation-tolerant FPGA, called the SpaceCube GR740 Host for Onboard Science and Telemetry (GHOST) architecture. The card will be designed to conform to the NASA Goddard Space Flight center (GSFC) CubeSat Card Specification (CS2), which provides a common template to build new 1U CubeSat-sized cards compatible with a variety of other avionics designs. The GR740 features a fault-tolerant quad- processor LEON4FT SPARC V8 integer unit with a 7-stage pipeline and 4×4 KiB instruction and data caches. To extend the capabilities of the GR740, the CertusPro-NX-RT, a low-power radiation-tolerant FPGA, was combined to create a hybrid system architecture, providing the benefits of a programmable logic fabric. The GHOST architecture supports high-reliability, general-purpose processing and system monitoring via the GR740 while simultaneously increasing the AI-based application performance via a combination of the GR740 and CertusPro-NX-RT.

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Industry 4.0 based Machine Learning Models for Anomalous Product Detection and Classification

Industry 4.0 based Machine Learning Models for Anomalous Pro...

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Emerging Trends in Industry 4.0 (ETI 4.0)

作者： Sourabh Kumar Saroj Kumar Chandra Ram Narayan Shukla Lipismita Panigrahi Center of Excellence in Industry 4.0 Computer Science and Engineering OP Jindal University Raigarh India Department of Computer Applications Kalinga Institute of Industrial Technology Bhubaneswar India

Automation has made tremendous changes in the industries. It has been used to automate the manual processes involved in different physical units of the industries. The purpose was to increase the production in the manufacturing. Now, computers are being used in the industries to monitor functionalities of different production units with the help of artificial intelligence and internet of things (IoT). The IoT has revolutionized the industries. It is an interconnected network system of physical units. The core purpose of it to gather and share information among different physical units. The IoT has great impact on the many areas such as business, industry, medicine, the economy, transport, industrial robots and automation systems. IoT with artificial intelligence has wide range of industrial applications. Industry 4.0 is used in the industries where different industrial units are connected over the internet and interacting to make decisions via machine-to-machine communication. It has increased the benefits of industries in terms of production and supply chain management. Manufacturing industry monitors its production units in every 10 milliseconds to capture features of the product that is being produced. The features generated in this process are huge in amount. Critical observation is performed on the generated features to categorize the product as anomalous or good. Product classification is difficult task in the labeled datasets due to human bias in labeling the final product as anomalous or good. In this work, machine learning models is being used to detect and classify faulty product produced by manufacturing industry. Both qualitative and quantitative study will be carried out to compare various machine learning models.

关键词： Manufacturing industries Biological system modeling Production Fourth Industrial Revolution Decision trees Biomedical monitoring Task analysis

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Adaptive Mixture Model Reduction based on the Composite Transportation Dissimilarity

Adaptive Mixture Model Reduction based on the Composite Tran...

引用

International Conference on Information Fusion

作者： Alessandro D’Ortenzio Costanzo Manes Vittorio De Iuliis Umut Orguner Department of Information Engineering Computer Science and Mathematics University of L’Aquila Center of Excellence EX-EMERGE University of L’Aquila Department of Electrical and Electronics Engineering Middle East Technical University Turkey

Providing efficient yet accurate statistical models is a challenging problem in many applications. When elementary models are not sufficiently descriptive, mixtures of densities can be used. A complexity management issue arises when mixture models are employed: the number of components should be a trade-off between the complexity and the accuracy of the model. However, in general, it is not obvious how to determine the right number of mixture components for a specific application. In a previous work, theoretical foundations to address such a topic have been laid, grounded on the use of the Composite Transportation Dissimilarity between mixtures, and a preliminary criterion to manage the complexity of a mixture model has been proposed. In this paper, additional theoretical insights are provided that allow to formulate a novel adaptive mixture reduction algorithm. Numerical tests show that in most cases the new algorithm constitutes a significant improvement over the previous one.

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Online Change Point Detection with Adaptive Learning for Multivariate Processes

SSRN

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SSRN 2024年

作者： Bourazas, Konstantinos Fokianos, Konstantinos Panayiotou, Christos G. Polycarpou, Marios Department of Mathematics and Statistics University of Cyprus Nicosia Cyprus Department of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus KIOS Research Innovation Center of Excellence University of Cyprus Nicosia Cyprus

Online change point detection for multivariate data is of great interest in a variety of fields. In order to achieve efficient detection, developed methodologies typically rely on assumptions that may not be met in practice. In this work, our objective is to provide an effective detection scheme for multivariate processes while relaxing the initial requirements as much as possible. We develop a CUSUM-type procedure for detecting persistent changes to the mean vector of the data in an online fashion. The proposed methodology is distribution free, and it is based on the Kernel Density Estimation. In addition, it is unsupervised, and adaptive in relation to the magnitude, or direction of a change. Furthermore, a post-alarm estimate for the change point location and the size of the shift detected is available. A simulation study evaluates its performance in comparison to a standard method for various shifts scenarios, while a data application demonstrates its use in practice. © 2024, The Authors. All rights reserved.

关键词： Multivariant analysis

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Report-Guided Cross-Modal Representation Learning for Predicting EGFR Mutations by Whole Slide Image

Report-Guided Cross-Modal Representation Learning for Predic...

引用

2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Qiao, Qi Shi, Jun Jiang, Zhiguo Wang, Wei Wu, Haibo Zheng, Yushan Hefei University of Technology School of Computer Science and Information Engineering Hefei230601 China Hefei University of Technology School of Software Hefei230601 China Beihang University Image Processing Center School of Astronautics Beijing102206 China University of Science and Technology of China Division of Life Sciences and Medicine Department of Pathology First Affiliated Hospital of Ustc Hefei230036 China University of Science and Technology of China Intelligent Pathology Institute Division of Life Sciences and Medicine Hefei230036 China Beihang University School of Engineering Medicine Beijing Advanced Innovation Center for Biomedical Engineering Beijing100191 China

ISBN: (纸本)9798350386226

Traditional PCR/NGS-based multigene panel testing is time-consuming and costly. Predicting EGFR mutations directly from H&E stained whole slide images (WSIs) can alleviate these limitations. Furthermore, histopathological reports contain valuable textual information that correlates with tissue areas in WSIs. However, recent research mainly analyses EGFR mutation status only from a single modality, ignoring rich information contained in reports. In this paper, we propose a report-guided cross-modal representation learning method for predicting EGFR mutations by WSIs. Specifically, we reconstruct report-level embeddings through exploring intrinsic relationships between diagnostic words in histopathological reports and tissue areas in WSIs. Finally, reconstructed histopathological report embedding and aggregated WSI embedding are fused for final prediction. More importantly, molecular testing report is also introduced as prior supervision information at the training stage to guarantee semantic consistency of fused feature and molecular report embedding. We evaluate our method on the TCGA-EGFR public benchmark dataset and an in-house clinical dataset (USTC-EGFR). Experimental results demonstrate that our method outperforms existing approaches in EGFR mutation prediction, highlighting the benefits of cross-modal learning in enhancing feature representational ability. The code is available at https://***/HFUT-miaLab/RCRL. © 2024 IEEE.

关键词： Supervised learning

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A New 8/14 Two-Phase Switched Reluctance Motor with Improved Performance

A New 8/14 Two-Phase Switched Reluctance Motor with Improved...

引用

Power Electronic and Drive Systems and Technologies Conference (PEDSTC)

作者： Gholamreza Davarpanah Hossein Shirzad Jawad Faiz Electrical Engineering Department Amirkabir University of Technology Tehran Iran Department of Electrical Engineering Shahid Beheshti University Tehran Iran Center of Excellence on Applied Electromagnetic Systems School of Electrical and Computer Engineering University of Tehran Tehran Iran

Despite their simple and robust structure, low cost, and simple cooling system, switched reluctance motors (SRMs) face the challenge of low mean torque. A possible solution is to change the structure of SRMs. This article introduces an innovative combination of the number of rotor teeth and stator teeth of a two-phase switch reluctance motor (TPSRM) with eight teeth for the stator and fourteen teeth for the rotor. As a result of its unique design, which has a short path for passing the main flux, it requires less magnetomotive force. This leads to less core and copper loss, resulting in increased efficiency. Each tooth of the stator in a phase develops a positive torque during the rotation of the rotor, which increases the torque and consequently increases the mean torque of the proposed TPSRM. For both motors, a current hysteresis control (CHC) is simulated using 2D-FEM with a current hysteresis reference of 15A at 600 rpm which is the rated speed and a DC link voltage of 150 V To verify the novelty and advantages of the suggested TPSRM, it is compared with the conventional 8/12 TPSRM in terms of mean and peak torque, torque density, and core and copper losses were compared. Lastly, the proposed 8/14 TPSRM is shown to have better performance than the conventional 8/12 TPSRM.

关键词： Couplings Stator cores Torque Magnetic cores Rotors Hysteresis motors Switched reluctance motors

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