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Progress in research on ultrasound radiomics for predicting the prognosis of breast cancer

Cancer Innovation 2023年第4期2卷 283-289页

作者： Xuantong Gong Xuefeng Liu Xiaozheng Xie Yong Wang Department of Ultrasound National Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBijingChina State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBejjing Advanced Innovation Center for Big Data and Brain Computing(BDBC)Beihang UniversityBeijingChina School of Computer and Communication Engi neering.University of Science and Technology Beijing BeijingChina

Breast cancer is the most common malignant tumor and the leading cause of cancer-related deaths in women *** means of predicting the prognosis of breast cancer are very helpful in guiding treatment and improving patients'*** extracted by radiomics reflect the genetic and molecular characteristics of a tumor and are related to its biological behavior and the patient's ***,radiomics provides a new approach to noninvasive assessment of breast cancer *** is one of the commonest clinical means of examining breast *** recent years,some results of research into ultrasound radiomics for diagnosing breast cancer,predicting lymph node status,treatment response,recurrence and survival times,and other aspects,have been *** this article,we review the current research status and technical challenges of ultrasound radiomics for predicting breast cancer *** aim to provide a reference for radiomics researchers,promote the development of ultrasound radiomics,and advance its clinical application.

关键词： breast cancer deeplearning prognosisprediction radiomics ultrasound

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Acoustic Amplifying Diode Using Nonreciprocal Willis Coupling

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Physical Review Letters 2023年第17期130卷 176101-176101页

作者： Xinhua Wen Heung Kit Yip Choonlae Cho Jensen Li Namkyoo Park Department of Physics The Hong Kong University of Science and Technology Kowloon Hong Kong China Photonic Systems Laboratory Department of Electrical and Computer Engineering Seoul National University Seoul 08826 South Korea

We propose a concept called acoustic amplifying diode combining signal isolation and amplification in a single device. The signal is exponentially amplified in one incident direction with no reflection and is perfectly absorbed in another. The reflection is eliminated from the device in both directions with impedance matching, preventing backscattering to the signal source. Here, we demonstrate the amplifying diode using an active metamaterial with nonreciprocal Willis coupling. We also discuss the situation with the presence of both reciprocal and nonreciprocal Willis couplings for more flexibility in implementation. The coexistence of both amplifier and perfect absorber in opposite incident directions extends the regime of sound isolation and further enables applications in sensing and communication, in which nonreciprocity can play an important role.

关键词： Acoustic metamaterials Non-Hermitean systems

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Towards Hierarchical Categorical Named Entity Recognition via Injective Multi-task Learning Strategy 8

Towards Hierarchical Categorical Named Entity Recognition vi...

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8th International Conference on Big Data and Information Analytics, BigDIA 2022

作者： Xiaoguang, Yuan Chaofan, Dai Youchen, Wang Yaokai, Cheng Zengwenpro, Yu Tianfeng, Du National University of Defense Technology Changsha China Beijing Institute of Computer Technology and Application Beijing China National University of Defense Technology Science and Technology on Information Systems Engineering Laboratory Changsha China School of Computer Science and Technology Xidian University Xi'an China School of Management and Engineering Captital University of Economics and Business Beijing China

ISBN: (数字)9781665487962

ISBN: (纸本)9781665487962

The Named Entity Recognition (NER) task aims to locate meaningful entities in a text and classify them into pre-defined categories. NER is a fundamental task in the field of natural language processing. In practice, entities often have multiple types at different levels of granularity, and it is essential to identify various levels of categories of entities simultaneously. A deep learning-based approach treats NER as a sequence annotation problem by giving each character a unique entity label, which significantly improves the accuracy of NER. Deep learning-based NER performs well on single-category and coarse-grained NER but does not perform well on hierarchical category NER problems. This paper proposes a multi-task learning-based hierarchical category named entity recognition model to solve this problem. The model uses a multi-task learning mechanism to simultaneously learn multiple levels of information of named entity recognition tasks. Named entity recognition results at higher levels are directly constructed from lower-level recognition structures. Experiments show that both systems can significantly improve the recognition performance at each level compared to the basic multi-tasking model. The model is also compared with each level's traditional named entity recognition method. The hierarchical category named entity recognition model can sig-nificantly improve the performance of named entity recognition tasks at each level. © 2022 IEEE.

关键词： Learning systems

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SEMANTICALLY-GUIDED DISENTANGLED REPRESENTATION FOR ROBUST GAIT RECOGNITION

SEMANTICALLY-GUIDED DISENTANGLED REPRESENTATION FOR ROBUST G...

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2021 IEEE International Conference on Multimedia and Expo, ICME 2021

作者： Chai, Tianrui Mei, Xinyu Li, Annan Wang, Yunhong State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing100191 China

ISBN: (纸本)9781665438643

Gait is an important biometric that can recognize people at a distance. Recently, Disentangled Representation Learning (DRL) has been introduced for distinguishing identity-irrelevant covariate features from identity features for better recognition performance. However, such a simple gait energy image (GEI) pairing operation inevitably brings in over-disentanglement effects that degrade the performance. To address this issue, we proposed a covariate feature control gate module that compensates for the discriminative feature loss by using additional semantic labels. Furthermore, a shared attention module, which allows the identity and covariate part to pay attention to different spatial regions, is also proposed for better spatial disentanglement. Experimental results show that our method outperforms the state-of-the-art and well-explain the mechanism of how the improvement is achieved. The code is available at https://***/ctrasd/GA-ICDNet. © 2021 IEEE

关键词： Semantics

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Priority-Driven Task Scheduling and Resource Allocation in Cloud Environment

Priority-Driven Task Scheduling and Resource Allocation in C...

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Ubiquitous Networking (UNet), International Conference on

作者： Hicham Ben Alla Said Ben Alla Abdellah Ezzati Mathematics and Computer Science Department LAVETE laboratory Science and Technical Faculty Hassan 1 University Settat Morocco Industrial Systems Engineering Department LAVETE laboratory National School of Applied Sciences - Berrechid Hassan 1 University Settat Morocco

ISBN: (数字)9798350356144

ISBN: (纸本)9798350356151

Currently, efficient task scheduling and resource allocation processes are crucial for optimizing performance in cloud computing environments. In this paper, we introduce a novel approach that prioritizes tasks based on their specific requirements and allocates resources accordingly. Task priority is determined through a scoring threshold that considers different requirements such as deadline, temporal requirements, and task length. To ensure efficient matching, virtual machines (VMs) are categorized into three distinct groups using K-means clustering. Simulations conducted within the CloudSim simulator demonstrate the effectiveness of this method, leading to significant reductions in makespan and energy consumption, while simultaneously improving resource utilization compared to existing algorithms.

关键词： Cloud computing Energy consumption Processor scheduling Computational modeling Clustering algorithms Dynamic scheduling Resource management

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Optimal Linear Deception Attacks on Remote State Estimation with Constrained Alarm Rates: A Low-Dimensional Case

Optimal Linear Deception Attacks on Remote State Estimation ...

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IEEE Conference on Decision and Control

作者： Jun Shang Hanwen Zhang Jing Zhou Tongwen Chen Department of Control Science and Engineering Shanghai Research Institute for Intelligent Autonomous Systems National Key Laboratory of Autonomous Intelligent Unmanned Systems and Frontiers Science Center for Intelligent Autonomous Systems Tongji University Shanghai China Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China Department of Electrical and Computer Engineering University of Alberta Edmonton AB Canada

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

This study addresses linear attacks on remote state estimation within the context of a constrained alarm rate. Smart sensors, which are equipped with local Kalman filters, transmit innovations instead of raw measurements through a wireless communication network. This transmission is vulnerable to malicious data interception and manipulation by attackers. The aim of this research is to identify the optimal attack strategy that degrades the system performance while adhering to stealthiness constraints. A notable innovation of this paper is the direct association of the attack’s stealthiness with the alarm rate, diverging from traditional approaches that rely on the covariance of the innovation or the Kullback–Leibler divergence, which are conventional metrics that have been extensively explored in previous studies. Our findings reveal that the optimal attack strategy exhibits some structural characteristics in systems of low dimensions. The performance of the proposed attack strategy is demonstrated through numerical examples.

关键词： Wireless communication Measurement Technological innovation System performance Kalman filters State estimation Intelligent sensors

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Stealthy Attacks on Sampled-Data Control and Encryption-Based Countermeasures

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IEEE Transactions on Automatic Control 2025年

作者： Shang, Jun Li, Yuzhe Chen, Tongwen Tongji University Department of Control Science and Engineering Shanghai Institute of Intelligent Science and Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Shanghai200092 China Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110004 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 1H9 Canada

This paper investigates stealthy attacks on sampled-data control systems, where a continuous process is sampled periodically, and the resultant discrete output and control signals are transmitted through dual channels in wireless communication networks. Acknowledging the vulnerability of these transmitted data to cyber threats, we analyze two types of stealthy attacks that compromise either one or both channels. We explicitly present the necessary and sufficient conditions for the existence of stealthy single-channel attacks. To mitigate these security risks, we implement encryption-based countermeasures, including linear time-invariant and periodic encryption methods. We detail sufficient conditions under which these encryption strategies effectively thwart single- and dual-channel stealthy attacks. The effectiveness of these approaches and the theoretical findings are demonstrated through numerical simulations. © 1963-2012 IEEE.

关键词： Cyber attacks

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CCT5: A Code-Change-Oriented Pre-Trained Model

arXiv

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arXiv 2023年

作者： Lin, Bo Liu, Yepang Wang, Shangwen Xia, Xin Liu, Zhongxin Mao, Xiaoguang College of Computer Science National University of Defense Technology Changsha China Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China Zhejiang University Hangzhou China Key Laboratory of Software Engineering for Complex Systems China Research Institute of Trustworthy Autonoumous Systems United Kingdom

Software is constantly changing, requiring developers to perform several derived tasks in a timely manner, such as writing a description for the intention of the code change, or identifying the defect-prone code changes. Considering that the cost of dealing with these tasks can account for a large proportion (typically around 70 percent) of the total development expenditure, automating such processes will significantly lighten the burdens of developers. To achieve such a target, existing approaches mainly rely on training deep learning models from scratch or fine-tuning existing pre-trained models on such tasks, both of which have weaknesses. Specifically, the former uses comparatively small-scale labelled data for training, making it difficult to learn and exploit the domain knowledge of programming language hidden in the large-amount unlabelled code in the wild;the latter is hard to fully leverage the learned knowledge of the pre-trained model, as existing pre-trained models are designed to encode a single code snippet rather than a code change (i.e., the difference between two code snippets). We propose to pre-train a model specially designed for code changes to better support developers in software maintenance. To this end, we first collect a large-scale dataset containing 1.5M+ pairwise data of code changes and commit messages. Based on these data, we curate five different tasks for pre-training, which equip the model with diverse domain knowledge about code changes. We fine-tune the pre-trained model, CCT5, on three widely-studied tasks incurred by code changes and two tasks specific to the code review process. Results show that CCT5 outperforms both conventional deep learning approaches and existing pre-trained models on these tasks. Copyright © 2023, The Authors. All rights reserved.

关键词： Domain Knowledge

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Orthogonal matrix of polarization combinations:concept and application to multichannel holographic recording

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Opto-Electronic Advances 2024年第10期7卷 4-13页

作者： Shujun Zheng Jiaren Tan Hongjie Liu Xiao Lin Yusuke Saita Takanori Nomura Xiaodi Tan Information Photonics Research Center College of Photonic and Electronic EngineeringFujian Normal UniversityFuzhou 350117China Department of Electrical and Computer Engineering Duke UniversityDurhamNC 27708USA College of Photonic and Electronic Engineering Key Laboratory of Opto-Electronic Science and for Medicine of Ministry of EducationFujian Provincial Key Laboratory of Photonics TechnologyFujian Provincial Engineering Technology Research Center of Photoelectric Sensing ApplicationFujian Normal UniversityFuzhou 350117China Faculty of Systems Engineering Wakayama University930 SakaedaniWakayama640-8510Japan.

Orthogonal matrices have become a vital means for coding and signal processing owing to their unique distributional *** orthogonal matrices based on amplitude or phase combinations have been extensively explored,the orthogonal matrix of polarization combinations(OMPC)is a novel,relatively unexplored ***,we propose a method for constructing OMPCs of any dimension encompassing 4n(where n is 1,2,4,8,…)mutually orthogonal 2ncomponent polarization *** the field of holography,the integration of polarization multiplexing techniques with polarization-sensitive materials is expected to emerge as a groundbreaking approach for multichannel hologram multiplexing,offering considerable enhancements in data storage capacity and security.A multidimensional OMPC enables the realization of multichannel multiplexing and dynamical modulation of information in polarization holographic *** consolidating all information into a single position within the material,we effectively avoided extraneous crosstalk during the reconstruction *** results show that achieving four distinct holographic images individually and simultaneously depends on the polarization combination represented by the incident *** discovery opens up a new avenue for achieving highly holographic information storage and dynamically displayed information,harnessing the potential of OMPC to expand the heretofore limited dimensionality of orthogonal polarization.

关键词： orthogonal matrix of polarization combinations polarization-modulated multiplexing multichannel recording polarization holography dynamical information modulation

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Phase Analysis of N-Port Electrical Networks under Interconnections

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IFAC-PapersOnLine 2023年第2期56卷 4295-4300页

作者： Jianqi Chen Wei Chen Li Qiu Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong China Department of Mechanics and Engineering Science & State Key Laboratory for Turbulence and Complex Systems Peking University Beijing 100871 China

We study a class of matrix operations induced by n-port electrical network interconnections. We first introduce the frequency-dependent phases of n-port linear time-invariant electrical networks in light of the recently defined phases of complex matrices. Such phase characterization can be used to, for example, qualify the well-known notion of passivity for networks in a way. Next, the intrinsic phase properties of networks under interconnections are investigated. A scalable phase-preserving criterion is presented. The criterion involves only the phase properties of individual sub-networks, under the matrix operations featured by interconnections, whereby the phase range of the newly integrated network can be verified effectively, and more importantly maintains the scalability of analysis.

关键词： N-port network Interconnection Matrix operation Phase preservation

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