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Environmental research 2025年 279卷 121909页

作者： G Palanisamy Nora Hamad Al-Shaalan K Bhuvaneswari G Bharathi G Bharath T Pazhanivel Sathishkumar V E Madan Kumar Arumugam S K Khadeer Pasha Mohamed A Habila Adel El-Marghany Department of Physics Periyar University Salem 636 011 Tamil Nadu India. Department of Chemistry College of Science Princess Nourah bint Abdulrahman University Riyadh 11671 Saudi Arabia. Key Laboratory of Optoelectronic Devices and Systems of Guangdong Province College of Optoelectronic Engineering Shenzhen University Shenzhen Guangdong Province 518060 PR China. Department of Chemical Engineering Khalifa University P.O. Box 127788 Abu Dhabi United Arab Emirates. Department of Computer Science and Engineering Kongu Engineering College Perundurai Erode 638101 Tamil Nadu India. Cancer Biology Lab Centre for Molecular and Nanomedical Sciences Sathyabama Institute of Science and Technology Chennai 600119 India. Department of Physics VIT-AP University Amaravati Guntur 522501 Andhra Pradesh India. Advanced Materials Research Chair Chemistry Department College of Science King Saud University Riyadh 11451 Saudi Arabia.

Mobile APP user attribute prediction by heterogeneous information network modeling

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arXiv 2019年

作者： Zhang, Hekai Gong, Jibing Teng, Zhiyong Wang, Dan Wang, Hongfei Du, Linfeng Bhuiyan, Zakirul Alam School of Information Science and Engineering Yanshan University Qinhuangdao066004 China Key Lab for Computer Virtual Technology and System Integration Yanshan University Qinhuangdao066004 China School of Computer Science and Engineering Beihang University Beijing100191 China Shenyuan Honors College Beihang University Beijing100191 China State Key Lab of Mathematical Engineering and Advanced Computing Wuxi214000 China Department of Computer and Information Sciences Fordham University

User-based attribute information, such as age and gender, is usually considered as user privacy information. It is difficult for enterprises to obtain user-based privacy attribute information. However, user-based privacy attribute information has a wide range of applications in personalized services, user behavior analysis and other aspects. Although many scholars have made achievements in user attribute prediction and other related fields, there are still two main problems that impede further improvement on the accuracy of classification: (1) Traditional machine learning classification merely takes each object as a single individual, ignoring the relationship between them;(2) At present, the popular Heterogeneous Path-Mine Information Network only considers whether the user has a relationship with the attributes of other nodes, rather than the degree of correlation of the attributes. It employs a linear regression model to fit the weight of meta-path, which is highly sensitive to outliers. To solve the above two problems, this paper advances the HetPathMine model and puts forward TPathMine model. With applying the number of clicks of attributes under each node to express the user's emotional preference information, optimizations of the solution of meta-path weight are also presented. Based on meta-path in heterogeneous information networks, the new model integrates all relationships among objects into isomorphic relationships of classified objects. Matrix is used to realize the knowledge dissemination of category knowledge among isomorphic objects. The experimental results show that: (1) the prediction of user attributes based on heterogeneous information networks can achieve higher accuracy than traditional machine learning classification methods;(2) TPathMine model based on the number of clicks is more accurate in classifying users of different age groups, and the weight of each meta-path is consistent with human intuition or the real world situation. Copyright ©

关键词： Forecasting

Reciprocity of thermal diffusion in time-modulated systems

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arXiv 2021年

作者： Li, Jiaxin Li, Ying Cao, Pei-Chao Zheng, Xu Peng, Yu-Gui Li, Baowen Zhu, Xue-Feng Alù, Andrea Qiu, Cheng-Wei Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore School of Mechatronics Engineering Harbin Institute of Technology Harbin150001 China Interdisciplinary Center for Quantum Information State Key Laboratory of Modern Optical Instrumentation College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China ZJU-Hangzhou Global Science and Technology Innovation Center Key Lab. of Advanced Micro Nano Electronic Devices & Smart Systems of Zhejiang Zhejiang University Hangzhou310027 China International Joint Innovation Center ZJU-UIUC Institute Electromagnetics Academy at Zhejiang University Zhejiang University Haining314400 China School of Physics and Innovation Institute Huazhong University of Science and Technology Wuhan430074 China Department of Physics University of Colorado BoulderCO80309 United States Department of Electrical Engineering City University of New York New YorkNY10031 United States Department of Mechanical Engineering University of Colorado BoulderCO80309 United States

The reciprocity principle governs the symmetry in transmission of electromagnetic and acoustic waves, as well as the diffusion of heat between two points in space, with important consequences for thermal management and energy harvesting. There has been significant recent interest in materials with time-modulated properties, which have been shown to efficiently break reciprocity for light, sound, and even charge diffusion. Quite surprisingly, here we show that, from a practical point of view, time modulation cannot generally be used to break reciprocity for thermal diffusion. We establish a theoretical framework to accurately describe the behavior of diffusive processes under time modulation, and prove that thermal reciprocity in dynamic materials is generally preserved by the continuity equation, unless some external bias or special material is considered. We then experimentally demonstrate reciprocal heat transfer in a time-modulated device. Our findings correct previous misconceptions regarding reciprocity breaking for thermal diffusion, revealing the generality of symmetry constraints in heat transfer, and clarifying its differences from other transport processes in what concerns the principles of reciprocity and microscopic reversibility. © 2021, CC BY.

关键词： Energy harvesting

Consistent discretization of a class of predefined-time stable systems

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arXiv 2020年

作者： Jiménez-Rodríguez, Esteban Aldana-López, Rodrigo Sánchez-Torres, Juan D. Gómez-Gutiérrez, David Loukianov, Alexander G. Department of Electrical Engineering Cinvestav-Guadalajara Jalisco45019 Mexico Department of Computer Science and Systems Engineering University of Zaragoza Zaragoza50009 Spain Research Laboratory on Optimal Design Devices and Advanced Materials -OPTIMA- Department of Mathematics and Physics ITESO Jalisco45604 Mexico Multi-agent autonomous systems lab Intel Labs Intel Tecnología de México Jalisco45019 Mexico Tecnologico de Monterrey Escuela de Ingeniería y Ciencias Jalisco45138 Mexico

As the main contribution, this document provides a consistent discretization of a class of fixed-time stable systems, namely predefined-time stable systems. In the unperturbed case, the proposed approach allows obtaining not only a consistent but exact discretization of the considered class of predefined-time stable systems, whereas in the perturbed case, the consistent discretization preserves the predefined-time stability property. All the results are validated through simulations and compared with the conventional explicit Euler scheme, highlighting the advantages of this proposal. Copyright © 2020, The Authors. All rights reserved.

关键词： Digital control systems

Learnable low-rank latent dictionary for subspace clustering

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Pattern Recognition 2021年 120卷

作者： Yesong Xu Shuo Chen Jun Li Lei Luo Jian Yang PCA Lab Key Lab of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education and Jiangsu Key Lab of Image and Video Understanding for Social Security School of Computer Science and Engineering Nanjing University of Science and Technology Jiangsu 210094 China RIKEN Center for Advanced Intelligence Project Tokyo 103-0027 Japan JD Finance America Corporation USA

Recently, Self-Expressive-based Subspace Clustering (SESC) has been widely applied in pattern clustering and machine learning as it aims to learn a representation that can faithfully reflect the correlation between data points. However, most existing SESC methods directly use the original data as the dictionary, which miss the intrinsic structure (e.g., low-rank and nonlinear) of the real-word data. To address this problem, we propose a novel Projection Low-Rank Subspace Clustering (PLRSC) method by integrating feature extraction and subspace clustering into a unified framework. In particular, PLRSC learns a projection transformation to extract the low-dimensional features and utilizes a low-rank regularizer to ensure the informative and important structures of the extracted features. The extracted low-rank features effectively enhance the self-expressive property of the dictionary. Furthermore, we extend PLRSC to a nonlinear version (i.e., NPLRSC) by integrating a nonlinear activator into the projection transformation. NPLRSC cannot only effectively extract features but also guarantee the data structure of the extracted features. The corresponding optimization problem is solved by the Alternating Direction Method (ADM), and we also prove that the algorithm converges to a stationary point. Experimental results on the real-world datasets validate the superior of our model over the existing subspace clustering methods.

关键词： Subspace clustering Low-rank Feature extraction Block diagonal representation

Poster: Semantically enhanced tag recommendation for software CQAs via deep learning 40

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Poster: Semantically enhanced tag recommendation for softwar...

40th ACM/IEEE International Conference on Software engineering, ICSE 2018

作者： Zhang, Jian Sun, Hailong Tian, Yanfei Liu, Xudong SKLSDE Lab School of Computer Science and Engineering Beihang University Beijing100191 China Beijing Advanced Innovation Center for Big Data and Brain Computing Beijing100191 China

ISBN: (纸本)9781450356633

Most software CQAs (e.g. Stack Overflow) mainly rely on users to assign tags for posted questions. This leads to many redundant, inconsistent and inaccurate tags that are detrimental to the communities. Therefore tag quality becomes a critical challenge to deal with. In this work, we propose STR, a deep learning based approach that automatically recommends tags through learning the semantics of both tags and questions in such software CQAs. First, word embedding is employed to convert text information to high-dimension vectors for better representing questions and tags. Second, a Multi-Tasking-like Convolutional Neural Network, the core modules of STR, is designed to capture short and long semantics. Third, the learned semantic vectors are fed into a gradient descent based algorithm for classification. Finally, we evaluate STR on three datasets collected from popular software CQAs, and experimental results show that STR outperforms state-of-The-Art approaches in terms of Precision@k, Recall@k and F1-Measure@k. © 2018 Authors.

关键词： Semantics

CholecTriplet2021: A benchmark challenge for surgical action triplet recognition

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arXiv 2022年

作者： Nwoye, Chinedu Innocent Alapatt, Deepak Yu, Tong Vardazaryan, Armine Xia, Fangfang Zhao, Zixuan Xia, Tong Jia, Fucang Yang, Yuxuan Wang, Hao Yu, Derong Zheng, Guoyan Duan, Xiaotian Getty, Neil Sanchez-Matilla, Ricardo Robu, Maria Zhang, Li Chen, Huabin Wang, Jiacheng Wang, Liansheng Zhang, Bokai Gerats, Beerend Raviteja, Sista Sathish, Rachana Tao, Rong Kondo, Satoshi Pang, Winnie Ren, Hongliang Abbing, Julian Ronald Sarhan, Mohammad Hasan Bodenstedt, Sebastian Bhasker, Nithya Oliveira, Bruno Torres, Helena R. Ling, Li Gaida, Finn Czempiel, Tobias Vilaça, João L. Morais, Pedro Fonseca, Jaime Egging, Ruby Mae Wijma, Inge Nicole Qian, Chen Bian, Guibin Li, Zhen Balasubramanian, Velmurugan Sheet, Debdoot Luengo, Imanol Zhu, Yuanbo Ding, Shuai Aschenbrenner, Jakob-Anton van der Kar, Nicolas Elini Xu, Mengya Islam, Mobarakol Seenivasan, Lalithkumar Jenke, Alexander Stoyanov, Danail Mutter, Didier Mascagni, Pietro Seeliger, Barbara Gonzalez, Cristians Padoy, Nicolas ICube University of Strasbourg CNRS France IHU Strasbourg France Department of Computer Science University of Chicago United States Lab for Medical Imaging and Digital Surgery Shenzhen Institute of Advanced Technology Chinese Academy of Sciences China School of Management Hefei University of Technology Hefei China Institue of Medical Robotics Shanghai Jiao Tong University Shanghai China Argonne National Laboratory 9700 S Cass Ave LemontIL60439 United States Digital Surgery A Medtronic Company London United Kingdom Institute of Automation Chinese Academy of Sciences China Department of Computer Science School of Informatics Xiamen University Xiamen China Johnson & Johnson Meander Medical Centre Netherlands Indian Institute of Technology Kharagpur India Muroran Institute of Technology Japan Department of Biomedical Engineering National University of Singapore Singapore Department for Translational Surgical Oncology National Center for Tumor Diseases Partner Site Dresden Germany 2Ai School of Technology IPCA Barcelos Portugal School of Medicine University of Minho Braga Portugal Algoritimi Center School of Engineering University of Minho Guimeraes Portugal Technical University of Munich Germany Department of Electronic Engineering The Chinese University of Hong Kong Hong Kong Wellcome EPSRC Center for Interventional and Surgical Science University College London United Kingdom Fondazione Policlinico Universitario Agostino Gemelli IRCCS Rome Italy University Hospital of Strasbourg France

Context-aware decision support in the operating room can foster surgical safety and efficiency by leveraging real-time feedback from surgical workflow analysis. Most existing works recognize surgical activities at a coarse-grained level, such as phases, steps or events, leaving out fine-grained interaction details about the surgical activity;yet those are needed for more helpful AI assistance in the operating room. Recognizing surgical actions as triplets of combination delivers comprehensive details about the activities taking place in surgical videos. This paper presents CholecTriplet2021: an endoscopic vision challenge organized at MICCAI 2021 for the recognition of surgical action triplets in laparoscopic videos. The challenge granted private access to the large-scale CholecT50 dataset, which is annotated with action triplet information. In this paper, we present the challenge setup and assessment of the state-of-the-art deep learning methods proposed by the participants during the challenge. A total of 4 baseline methods from the challenge organizers and 19 new deep learning algorithms by competing teams are presented to recognize surgical action triplets directly from surgical videos, achieving mean average precision (mAP) ranging from 4.2% to 38.1%. This study also analyzes the significance of the results obtained by the presented approaches, performs a thorough methodological comparison between them, in-depth result analysis, and proposes a novel ensemble method for enhanced recognition. Our analysis shows that surgical workflow analysis is not yet solved, and also highlights interesting directions for future research on fine-grained surgical activity recognition which is of utmost importance for the development of AI in surgery. © 2022, CC BY-NC-SA.

关键词： Deep learning

An Algorithm for Full-Coverage Voltage-Conversion-Ratio Fibonacci-Like Charge Pump

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An Algorithm for Full-Coverage Voltage-Conversion-Ratio Fibo...

2018 IEEE International Conference on Electron Devices and Solid State Circuits, EDSSC 2018

作者： Liu, Binjie Lin, Hesheng Ding, Dedong Zhang, Dewei Zhang, Min Shenzhen Key Lab of Advanced Electron Device and Integration School of Electronic and Computer Engineering Peking University Shenzhen518055 China Imec-KU Leuven Leuven3001 Belgium

ISBN: (纸本)9781538662342

In this work, an algorithm for full-coverage voltage-conversion-ratio (VCR) Fibonacci-like charge pump is proposed. By shifting the connect node of each flying capacitor's bottom plate, a charge pump topology can achieve arbitrary integer voltage conversion ratios. By the algorithm, we can find the best Fibonacci-like charge pump topology with the least number of capacitors and transistors, for a given VCR. © 2018 IEEE.

关键词： Topology

A High-Efficient, Multi-Phase Charge Pump Scheme

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A High-Efficient, Multi-Phase Charge Pump Scheme

2018 IEEE International Conference on Electron Devices and Solid State Circuits, EDSSC 2018

作者： Zhang, Dewei Liu, Binjie Lin, Hesheng Ding, Dedong Zhang, Min Shenzhen Key Lab of Advanced Electron Device and Integration School of Electronic and Computer Engineering Peking University Shenzhen518055 China Imec-KU Leuven Leuven3001 Belgium

ISBN: (纸本)9781538662342

In this paper, a high-efficiency solution to multi-phase stepup charge pump is proposed. Aiming at traditional multi-phase charge pump with full-coverage integer voltage conversion ratios (VCRs) for good efficiency, we further improve its efficiency at some particular VCRs. By automatically bypassing some unnecessary converter stages, dynamic power loss is reduced. Based on a 0.25 μm process, an example of three-stage charge pump with VCRs of 1∼8 is conducted. It shows that converter with proposed control strategy has improved perofrmance at VCR © 2018 IEEE.

关键词： Efficiency

An On-Chip Oscillator with Comparator Offset Cancellation

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An On-Chip Oscillator with Comparator Offset Cancellation

2018 IEEE International Conference on Electron Devices and Solid State Circuits, EDSSC 2018

作者： Zhang, Dewei Zhang, Ruijun Lin, Hesheng Wang, Qinghua Zhang, Min Shenzhen Key Lab of Advanced Electron Device and Integration School of Electronic and Computer Engineering Peking University Shenzhen 518055 China Imec-KU Leuven Leuven3001 Belgium

ISBN: (纸本)9781538662342

This work presents an on-chip oscillator with offset cancellation in 0.25 μ m process. By automatically choosing the reference voltage in a single comparator, the proposed oscillator can perfectly achieve offset cancellation. In addition, it reduces the comparator count from two to one for area-saving and power-saving. The simulation results exhiUit a Temperature Coefficient of 2.3 ppm/oC from-40 to 90° c while consuming 6.5 μ W at 30 kHz. © 2018 IEEE.

关键词： Comparators (optical)