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TechRxiv 2020年

作者： Ren, Wei School of Computer Science China University of Geosciences Wuhan430074 China Key Laboratory of Network Assessment Technology CAS Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China Guizhou Provincial Key Laboratory of Public Big Data GuiZhou University Guizhou China

All primes can be indexed by k, as primes must be in the form of 6k+1 or 6k-1. In this paper, we explore for the set of k such that either 6k+1 or 6k-1 is not a prime. Our method provides a uniform formula for k that can sieve primes and twin primes as well. The uniform presents symmetry in terms of k that works as single index in sieving. We also propose a new conjecture that is equivalent to Twin Prime Conjecture but possibly be easier to approach by merely exploring of sole index in term of k. The uniform formula for prime sieving are as follows: k ∈ Sl ⇒ 6k−1 6∈ , where Sl = [−I]6I+1 = [I]6I−1\min([I]6I−1), I ∈ . k ∈ Sr ⇒ 6k + 1 6∈ , where Sr = [−I]6I−1 ∪ ([I]6I+1\min([I]6I+1)), I ∈ . © 2020, CC BY.

关键词： Number theory

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Deep plug-and-play priors for spectral snapshot compressive imaging

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Photonics Research 2021年第2期9卷 I0011-I0022页

作者： SIMING ZHENG YANG LIU ZIYI MENG MU QIAO ZHISHEN TONG XIAOYU YANG SHENSHENG HAN XIN YUAN Computer Network Information Center Chinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of TechnologyCambridgeMassachusetts 02139USA Beijing University of Posts and Telecommunications Beijing 100876China New Jersey Institute of Technology New Jersey 07102USA Key Laboratory for Quantum Optics and Center for Cold Atom Physics of CAS Shanghai Institute of Optics and Fine MechanicsChinese Academy of SciencesShanghai 201800China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijing 100049China Nokia Bell Labs Murray HillNew Jersey 07974USA

We propose a plug-and-play(Pn P) method that uses deep-learning-based denoisers as regularization priors for spectral snapshot compressive imaging(SCI). Our method is efficient in terms of reconstruction quality and speed trade-off, and flexible enough to be ready to use for different compressive coding mechanisms. We demonstrate the efficiency and flexibility in both simulations and five different spectral SCI systems and show that the proposed deep Pn P prior could achieve state-of-the-art results with a simple plug-in based on the optimization framework. This paves the way for capturing and recovering multi-or hyperspectral information in one snapshot,which might inspire intriguing applications in remote sensing, biomedical science, and material science. Our code is available at: https://***/zsm1211/Pn P-casSI.

关键词： spectral Deep plug

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A Dual-Channel Framework for Sarcasm Recognition by Detecting Sentiment Conflict

arXiv

引用

arXiv 2021年

作者： Liu, Yiyi Wang, Yequan Sun, Aixin Meng, Xuying Li, Jing Guo, Jiafeng CAS Key Lab of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Beijing Academy of Artificial Intelligence Beijing China School of Computer Science and Engineering Nanyang Technological University Singapore Singapore Institute of Computing Technology Chinese Academy of Sciences Beijing China Inception Institute of Artificial Intelligence Abu Dhabi United Arab Emirates

Sarcasm employs ambivalence, where one says something positive but actually means negative, and vice versa. The essence of sarcasm, which is also a sufficient and necessary condition, is the conflict between literal and implied sentiments expressed in one sentence. However, it is difficult to recognize such sentiment conflict because the sentiments are mixed or even implicit. As a result, the recognition of sophisticated and obscure sentiment brings in a great challenge to sarcasm detection. In this paper, we propose a Dual-Channel Framework by modeling both literal and implied sentiments separately. Based on this dual-channel framework, we design the Dual-Channel network (DC-Net) to recognize sentiment conflict. Experiments on political debates (i.e., IAC-V1 and IAC-V2) and Twitter datasets show that our proposed DC-Net achieves state-of-the-art performance on sarcasm recognition. Our code is released to support research https://***/yiyi-ict/dual-channel-for-sarcasm. © 2021, CC BY.

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Adversity-Based Social Circles Inference via Context-Aware Mobility

Adversity-Based Social Circles Inference via Context-Aware M...

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GLOBECOM 2020 - 2020 IEEE Global Communications Conference

作者： Qiang Gao Fan Zhou Goce Trajcevski Fengli Zhang Xucheng Luo Network and Data Security Key Laboratory of Sichuan Province China University of Electronic Science and Technology of China China Iowa State University Ames USA

ISBN: (数字)9781728182988

ISBN: (纸本)9781728182995

The ubiquity of mobile devices use has generated huge volumes of location-aware contextual data, providing opportunities enriching various location-based social network (LBSN) applications - e.g., trip recommendation, ride-sharing allocation and taxi demand prediction etc. Trajectory-based social circle inference (TSCI), which aims at inferring the social relationships among users based on the human mobility data, has received great attention in recent years due to its importance in many LBSN applications. However, existing solutions suffer from three key challenges, including (1) lack of modeling contextual feature in user check-ins; (2) cannot capture the structural information in user motion patterns; (3) and fail to consider the underlying mobility distribution. In this paper, we propose a novel framework ASCI-CAM (Adversity-based Social Circles Inference via Context-Aware Mobility) to address the above challenges. ASCI-CAM is a graph-based model taking into account the contextual information associated with check-ins which, combined with an attentive auto-encoder, allows for semantic trajectory representation. We regularize the learned trajectory embedding with an adversarial learning procedure, which allows us to better understand the user mobility patterns and personalized trajectory distribution. Our extensive experiments on real-world mobility datasets demonstrate that our model achieves significant improvement over the state-of-the-art baselines.

关键词： Trajectory Social networking (online) Training Task analysis Semantics Logic gates Training data

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Context-Aware Feature Attention Model for Coreference Resolution on Biomedical Texts

Research Square

引用

Research Square 2021年

作者： Li, Yufei Zhou, Xiangyu Ma, Jie Ma, Xiaoyong Li, Chen School of Computer Science and Technology Xi’an Jiaotong University Shaanxi Xi’an China National Engineering Lab for Big Data Analytics Xi’an Jiaotong University Shaanxi Xi’an China Shaanxi Province Key Laboratory of Satellite and Terrestrial Network Technology Research and Development Xi’an Jiaotong University Shaanxi Xi’an China

Background: Bio-entity Coreference resolution is an important task to gain a complete understanding of biomedical texts automatically. Previous neural network-based studies on this topic are domain system based methods which rely on some domain-specific information integration. However, for the identical mentions, this may lead to misleading information, as the model tends to get similar or even identical representations, which further leads to wrongful predictions. Results: we propose a new context-aware Feature Attention model to distinguish identical mentions effectively to better resolve coreference. The new model can represent identical mentions based on different contexts by adaptively exploiting features effectively. The proposed model substantially outperforms the state-of-the-art baselines on the BioNLP dataset with a 64.0% F1 score and further demonstrates superior performance on the differential representation and coreferential link of identical mentions. Conclusion: The context-aware Feature Attention model adaptively exploit features and represent identical mentions according to different contexts, which significantly makes the system obtain semantic information effectively and make more accurate predictions. Considering that this approach is still limited when context information is insufficient, we expect to utilize such information more fine-grained with the help of the external knowledge base in coreference resolution. © 2021, CC BY.

关键词： Semantics

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Optimization from Structured Samples for Coverage Functions

arXiv

引用

arXiv 2020年

作者： Chen, Wei Sun, Xiaoming Zhang, Jialin Zhang, Zhijie Microsoft Research Asia Beijing China CAS Key Lab of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences Beijing China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing China

We revisit the optimization from samples (OPS) model, which studies the problem of optimizing objective functions directly from the sample data. Previous results showed that we cannot obtain a constant approximation ratio for the maximum coverage problem using polynomially many independent samples of the form {Si, f (Si)}ti=1 (Balkanski et al., 2017), even if coverage functions are (1 − ǫ)-PMAC learnable using these samples (Badanidiyuru et al., 2012), which means most of the function values can be approximately learned very well with high probability. In this work, to circumvent the impossibility result of OPS, we propose a stronger model called optimization from structured samples (OPSS) for coverage functions, where the data samples encode the structural information of the functions. We show that under three general assumptions on the sample distributions, we can design efficient OPSS algorithms that achieve a constant approximation for the maximum coverage problem. We further prove a constant lower bound under these assumptions, which is tight when not considering computational efficiency. Moreover, we also show that if we remove any one of the three assumptions, OPSS for the maximum coverage problem has no constant approximation. Copyright © 2020, The Authors. All rights reserved.

关键词： Machine learning

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A Multi-Scale Two-Branch Fusion network for Simultaneous Segmentation in Electronic Laryngoscope Images

SSRN

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SSRN 2023年

作者： Chen, Hao Hao, Mayang Wang, Chenwu Wang, Pei School of Computer Science and Technology Xi’an University of Posts and Telecommunications 563 South Changan Road Yanta District Shaanxi Xi’an710061 China Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing Xi’an University of Posts and Telecommunications 563 South Changan Road Yanta District Shaanxi Xi’an710061 China School of Modern Post Xi’an University of Posts and Telecommunications 563 South Changan Road Yanta District Shaanxi Xi’an710061 China School of Computer Science Northwestern Polytechnical University 127 West Youyi Road Beilin District Shaanxi Xi’an710072 China

Three issues reduced the performance of networks for handling the organs and lesions’ simultaneous segmentation in electronic laryngoscopy images. Firstly, the moving endoscope will cause noticeable variations of the shape and angle in lesions and organs. Secondly, the lesions, mainly the polyps, and the major organs differ considerably in size. Moreover, the boundaries between the lesions or organs and their backgrounds are usually indistinguishable since their color and texture are very close to the mucosal tissues. To improve the simultaneous segmentation accuracy, we propose a multi-scale two-branch fusion network (MsFusionNet), which adopted an asymmetric two-branch structure to fuse the fine-grained feature maps extracted by the convolution neural network with the global context feature maps extracted by the Vision Transformer at different scales. In addition, a Multi-scale Dark Part Feature Enhancement module (MsDFE) was designed to enhance the non-salient details of organs before the feature fusion in the two-branch network. To evaluate the universality and effectiveness of the proposed method, we used a mixed dataset collected from three institutions, including 2425 electronic laryngoscope images with major organs in the pharynx and larynx. The results show the proposed method performs better than nine existing segmentation networks in dealing with the experiment dataset, which has good potential for clinical practice. © 2023, The Authors. All rights reserved.

关键词： Image enhancement

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Evaluating the Cache Side Channel Attacks Against ECDSA 15th

Evaluating the Cache Side Channel Attacks Against ECDSA

引用

15th International Conference on Information Security and Cryptology, Inscrypt 2019

作者： Ma, Ziqiang Cai, Quanwei Lin, Jingqiang Jing, Jiwu Ye, Dingfeng Meng, Lingjia State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing China Data Assurance and Communication Security Research Center CAS Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9783030429201

Various attacks are proposed against different ECDSA implementations: the key-related data are acquired through cache side channels, and then processed to recover the private key. For each cache side channel attack, the requirements of the data qualified for sequent processing vary greatly, and the success probability of private key recovery relies on both the acquired data and the parameters of data processing. So it is difficult to tell, for a certain ECDSA implementation, (a) how many signatures does a cache side channel attack need to recover the private key? or which attack performs the best? and (b) what kind of threat level exists due to potential side channel attacks, if the ECDSA implementation runs for a number of signatures on an unprotected system with cache side channels? Currently, there is no quantitative metric to fairly answer the questions. Such a metric to evaluate cache side channel attacks, will provide a reference for the adversaries to choose the suitable attack, and also for the defenders to set up protections for the certain ECDSA implementation (e.g., updating the private key after it has been used for a certain number of signatures). In this paper, we design an evaluation approach to quantitatively compare the cache side channel attacks against ECDSA. The expected minimum number of signatures needed for at least one successful private key recovery, is proposed as the metric, and this metric considers both the data requirements and the success probability. We apply the approach to evaluate various cache side channel attacks against ECDSA. By calculating the metric, we obtain (a) for each attack, the optimal parameters with the minimum number of signatures needed, and (b) for each ECDSA implementation, the minimum number of signatures that will be enough for at least one successful private key recovery of some cache side channel attacks. © 2020, Springer Nature Switzerland AG.

关键词： Side channel attack

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Quantitative modeling of bacterial quorum sensing dynamics in time and space

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Chinese Physics B 2020年第10期29卷 1-8页

作者： Xiang Li Hong Qi Xiao-Cui Zhang Fei Xu Zhi-Yong Yin Shi-Yang Huang Zhao-Shou Wang Jian-Wei Shuai Department o f Physics College o f Physical Science and TechnologyXiamen UniversityXiamen 361005China State Key Laboratory o f Cellular Stress Biology Innovation Center for Cell Signaling NetworkXiamen UniversityXiamen 361102China Complex Systems Research Center Shanxi UniversityTaiyuan 030006China Institute o f Biochemical Engineering Department o f Chemical and Biochemical EngineeringCollege o f Chemistry and Chemical EngineeringXiamen UniversityXiamen 361005China National Institute for Data Science in Health and Medicine Xiamen UniversityXiamen 361102China

Quorum sensing (QS) refers to the cell communication through signaling molecules that regulate many important biological functions of bacteria by monitoring their population density. Although a wide spectrum of studies on the QS system mechanisms have been carried out in experiments, mathematical modeling to explore the QS system has become a powerful approach as well. In this paper, we review the research progress of network modeling in bacterial QS to capture the system's underlying mechanisms. There are four types of QS system models for bacteria: the Gram-negative QS system model, the Gram-positive QS system model, the model for both Gram-negative and Gram-positive QS system, and the synthetic QS system model. These QS system models are mostly described by the ordinary differential equations (ODE) or partial differential equations (PDE) to study the changes of signaling molecule dynamics in time and space and the cell population density variations. Besides the deterministic simulations, the stochastic modeling approaches have also been introduced to discuss the noise effects on kinetics in QS systems. Taken together, these current modeling efforts advance our understanding of the QS system by providing systematic and quantitative dynamics description, which can hardly be obtained in experiments.

关键词： hacterial quorum sensing signaling molecules mathematical modeling dynamic analysis

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Utility maximization for multihop wireless networks employing BATS codes

arXiv

引用

arXiv 2021年

作者： Dong, Yanyan Jin, Sheng Chen, Yanzuo Yang, Shenghao Yin, Hoover H.F. The School of Science and Engineering The Chinese University of Hong Kong Shenzhen China Carnegie Mellon University The N-hop Technologies Limited Hong Kong The Institute of Network Coding The Chinese University of Hong Kong Hong Kong Shenzhen Key Laboratory of IoT Intelligent Systems and Wireless Network Technology Shenzhen Research Institute of Big Data Shenzhen China

BATS (BATched Sparse) codes are a class of efficient random linear network coding variation that has been studied for multihop wireless networks mostly in scenarios of a single communication flow. Towards sophisticated multi-flow network communications, we formulate a network utility maximization (NUM) problem that jointly optimizes the BATS code parameters of all the flows and network scheduling. The NUM problem adopts a batch-wise packet loss model that can be obtained from the network local statistics without any constraints on packet loss patterns. Moreover, the NUM problem allows a different number of recoded packets to be transmitted for different batches in a flow, which is called adaptive recoding. Due to both the probably nonconcave objective and the BATS code-related variables, the algorithms developed for the existing flow optimization problems cannot be applied directly to solve our NUM problem. We introduce a two-step algorithm to solve our NUM problem, where the first step solves the problem with nonadaptive recoding schemes, and the second step optimizes adaptive recoding hop-by-hop from upstream to downstream in each flow. We perform various numerical evaluations and simulations to verify the effectiveness and efficiency of the algorithm. © 2021, CC BY-NC-ND.

关键词： Packet loss

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