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Robust zero-watermarking algorithm based on discrete wavelet transform and daisy descriptors for encrypted medical image

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CAAI Transactions on Intelligence Technology 2024年第1期9卷 40-53页

作者： Yiyi Yuan Jingbing Li Jing Liu Uzair Aslam Bhatti Zilong Liu Yen-wei Chen School of Information and Communication Engineering Hainan UniversityHaikouChina research center for Healthcare data Science Zhejiang LabHangzhouChina Graduate School of Information Science and Engineering Ritsumeikan University ShigaJapan

In the intricate network environment,the secure transmission of medical images faces challenges such as information leakage and malicious tampering,significantly impacting the accuracy of disease diagnoses by medical *** address this problem,the authors propose a robust feature watermarking algorithm for encrypted medical images based on multi-stage discrete wavelet transform(DWT),Daisy descriptor,and discrete cosine transform(DCT).The algorithm initially encrypts the original medical image through DWT-DCT and Logistic ***,a 3-stage DWT transformation is applied to the encrypted medical image,with the centre point of the LL3 sub-band within its low-frequency component serving as the sampling *** Daisy descriptor matrix for this point is then ***,a DCT transformation is performed on the Daisy descriptor matrix,and the low-frequency portion is processed using the perceptual hashing algorithm to generate a 32-bit binary feature vector for the medical *** scheme utilises cryptographic knowledge and zero-watermarking technique to embed watermarks without modifying medical images and can extract the watermark from test images without the original image,which meets the basic re-quirements of medical image *** embedding and extraction of water-marks are accomplished in a mere 0.160 and 0.411s,respectively,with minimal computational *** results demonstrate the robustness of the algorithm against both conventional attacks and geometric attacks,with a notable performance in resisting rotation attacks.

关键词： daisy descriptor DCT DWT encryption domain medical image zero-watermarking

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地球大数据及其推动可持续发展的作用

Science Bulletin 2024年第11期69卷 1623-1627页

作者：郭华东梁栋 International research center of big data for Sustainable Development Goals Beijing 100094China Aerospace Information research Institute Chinese Academy of SciencesBeijing 100094China University of Chinese Academy of Sciences Beijing 100049China

The information age has been a product of, and has been fueled by, the process of decades-long digitization aided by digital technologies that progressed rapidly, consequently transforming human societies globally.

关键词：大数据 globally digit

Two kinds of average approximation accuracy

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CAAI Transactions on Intelligence Technology 2024年第2期9卷 481-490页

作者： Qingzhao Kong Wanting Wang Dongxiao Zhang Wenbin Zhang Department of Science Jimei UniversityXiamenChina Digital Fujian big data Modeling and Intelligent Computing Institute Jimei UniversityXiamenChina Department of Computer Science Michigan Technological UniversityHoughtonMichiganUSA

Rough set theory places great importance on approximation accuracy,which is used to gauge how well a rough set model describes a target ***,traditional approximation accuracy has limitations since it varies with changes in the target concept and cannot evaluate the overall descriptive ability of a rough set *** overcome this,two types of average approximation accuracy that objectively assess a rough set model’s ability to approximate all information granules is *** first is the relative average approximation accuracy,which is based on all sets in the universe and has several basic *** second is the absolute average approximation accuracy,which is based on undefinable sets and has yielded significant *** also explore the relationship between these two types of average approximation ***,the average approximation accuracy has practical applications in addressing missing attribute values in incomplete information tables.

关键词： rough sets rough set theory

Inflammatory Factor IL1αInduces Aberrant Astrocyte Proliferation in Spinal Cord Injury Through the Grin2c/Ca^(2+)/CaMK2b Pathway

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Neuroscience Bulletin 2024年第4期40卷 421-438页

作者： Yu Xia Lu Ding Changlin Zhang Qi Xu Ming Shi Tianshun Gao Feng-Quan Zhou David Y.B.Deng Scientific research center The Seventh Affiliated Hospital of Sun Yat-sen UniversityShenzhen518107China Department of Gynecology The Seventh Affiliated Hospital of Sun Yat-sen UniversityShenzhen518107China Pelvic Floor Disorders center The Seventh Affiliated Hospital of Sun Yat-sen UniversityShenzhen518107China big data center The Seventh Affiliated Hospital of Sun Yat-sen UniversityShenzhen518107China Sir Run Run Shaw Hospital Zhejiang University School of MedicineHangzhou310016China Orthopaedic and Neurological Repair center The Seventh Affiliated Hospital of Sun Yat-sen UniversityShenzhen518107China

Spinal cord injury(SCI)is one of the most devastating traumas,and the aberrant proliferation of astrocytes usually causes neurological ***,the mechanism underlying astrocyte over-proliferation after SCI is ***2c(glutamate ionotropic receptor type 2c)plays an essential role in cell *** bioinformatic analysis indicated that Grin2c and Ca^(2+)transport functions were inhibited in astrocytes after *** of Grin2c stimulated astrocyte proliferation by inhibiting the Ca^(2+)/calmodulin-dependent protein kinase 2b(CaMK2b)pathway in *** screening different inflammatory factors,interleukin 1α(IL1α)was further found to inhibit Grin2c/Ca^(2+)/CaMK2b and enhance astrocyte proliferation in an oxidative damage *** of IL1αusing neutralizing antibody resulted in increased Grin2c expression and the inhibition of astrocyte proliferation ***,this study suggests that IL1αpromotes astrocyte proliferation by suppressing the Grin2c/Ca^(2+)/CaMK2b pathway after SCI,revealing a novel pathological mechanism of astrocyte proliferation,and may provide potential targets for SCI repair.

关键词： IL1α Grin2c Astrocyte Spinal cord injury

Value-added Tax and Leverage:Evidence from China's Value-added Tax Rate Reform

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China & World Economy 2024年第2期32卷 200-234页

作者： Hongsheng Fang Lexin Zhao Xiufen Liu School of Economics and Institute for Fiscal Big-Data and PolicyZhejiang UniversityChina School of Economics Zhejiang UniversityChina School of Business Hangzhou City UniversityChina

This paper uses China's value-added tax(VAT)rate reform as a quasi-natural experiment to identify the impacts of VAT rate shocks on corporate financial *** results indicate that the reform reduced corporate total leverage *** was a decrease in short-term leverage,but long-term leverage showed no significant *** results remained robust across a series of robustness *** analysis shows that increasing profitability and improving cash flows acted as intermediary channels for the reform's impact on *** reform also contributed to the mitigation of the asset–liability mismatch problem and the reduction of debt risk,while having no apparent impact on corporate ***,enterprises with more elastic demand and those with lower intermediate input ratios were affected most by the deleveraging effect of the VAT rate *** study suggests how the VAT rate cut shaped corporate capital *** thus helps to explain the economic consequences of VAT rate shocks.

关键词： asset-liability ratio capital structure tax reduction VAT rate reform

Pregnancy and the disease recurrence of patients previously treated for differentiated thyroid cancer:A systematic review and meta analysis

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Chinese Medical Journal 2024年第5期137卷 547-555页

作者： Rui Shan Xin Li Ming Tao Wucai Xiao Jing Chen Fang Mei Shibing Song Bangkai Sun Chunhui Yuan Zheng Liu Department of Maternal and Child Health School of Public HealthPeking UniversityBeijing 100191China Department of General Surgery Peking University Third HospitalBeijing 100191China Department of Pathology Peking University Third HospitalSchool of Basic Medical SciencesPeking University Health Science CenterBeijing 100191China Information Management and big data center Peking University Third HospitalBeijing 100191China

Background:Differentiated thyroid cancer(DTC)is commonly diagnosed in women of child-bearing age,but whether pregnancy influences the prognosis of DTC remains *** study aimed to summarize existing evidence regarding the association of pregnancy with recurrence risk in patients previously treated for ***:We searched PubMed,Embase,Web of Science,Cochrane,and Scopus based on the prespecified protocol registered at PROSPERO(CRD42022367896).After study selection,two researchers independently extracted data from the included *** quantitative data synthesis,we used random-effects meta-analysis models to pool the proportion of recurrence(for pregnant women only)and odds ratio(OR;comparing the risk of recurrence between the pregnancy group and the nonpregnancy group),*** we conducted subgroup analyses to explore whether risk of recurrence differed by response to therapy status or duration of follow-up *** also assessed quality of the included ***:A total of ten studies were *** sample size ranged from 8 to 235,with participants’age at pregnancy or delivery ranging from 28 to 35 *** follow-up time varied from 0.1 to 36.0 *** pooled proportion of recurrence in all pregnant patients was 0.13(95%confidence intervals[CI]:0.06-0.25;I^(2):0.58).Among six included studies reporting response to therapy status before pregnancy,we observed a trend for increasingly higher risk of recurrence from excellent,indeterminate,and biochemically incomplete to structurally incomplete response to therapy(P trend0.05)or the OR of recurrence in studies with a comparison group(P>0.05).Two included studies t

关键词： Thyroid cancer Pregnancy Recurrence Women Systematic review Meta-analysis

Identity-Preserving Adversarial Training for Robust Network Embedding

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Journal of Computer Science & Technology 2024年第1期39卷 177-191页

作者：岑科廷沈华伟曹婍徐冰冰程学旗 data Intelligence System research center Institute of Computing TechnologyChinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 101480China Beijing Academy of Artificial Intelligence Beijing 100000China Chinese Academy of Sciences Key Laboratory of Network data Science and Technology Institute of Computing Technology Chinese Academy of SciencesBeijing 100190China

Network embedding,as an approach to learning low-dimensional representations of nodes,has been proved extremely useful in many applications,e.g.,node classification and link ***,existing network embed-ding models are vulnerable to random or adversarial perturbations,which may degrade the performance of network em-bedding when being applied to downstream *** achieve robust network embedding,researchers introduce adversari-al training to regularize the embedding learning process by training on a mixture of adversarial examples and original ***,existing methods generate adversarial examples heuristically,failing to guarantee the imperceptibility of generated adversarial examples,and thus limit the power of adversarial *** this paper,we propose a novel method Identity-Preserving Adversarial Training(IPAT)for network embedding,which generates imperceptible adversarial exam-ples with explicit identity-preserving *** formalize such identity-preserving regularization as a multi-class classification problem where each node represents a class,and we encourage each adversarial example to be discriminated as the class of its original *** experimental results on real-world datasets demonstrate that our proposed IPAT method significantly improves the robustness of network embedding models and the generalization of the learned node representations on various downstream tasks.

关键词： network embedding identity-preserving adversarial training adversarial the example

Deep learning-based semantic segmentation of human features in bath scrubbing robots

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Biomimetic Intelligence & Robotics 2024年第1期4卷 70-79页

作者： Chao Zhuang Tianyi Ma Bokai Xuan Cheng Chang Baichuan An Minghuan Yin Hao Sun School of Artificial Intelligence and data Science Hebei University of TechnologyTianjin 300401China Engineering research center of Intelligent Rehabilitation Device and Detection Technology Ministry of EducationTianjin 300401China

With the rise in the aging population,an increase in the number of semidisabled elderly individuals has been noted,leading to notable challenges in medical and healthcare,exacerbated by a shortage of nursing *** study aims to enhance the human feature recognition capabilities of bath scrubbing robots operating in a water fog *** investigation focuses on semantic segmentation of human features using deep learning ***,3D point cloud data of human bodies with varying sizes are gathered through light detection and ranging to establish human ***,a hybrid filtering algorithm was employed to address the impact of the water fog environment on the modeling and extraction of human ***,the network is refined by integrating the spatial feature extraction module and the channel attention module based on *** results indicate that the algorithm adeptly identifies feature information for 3D human models of diverse body sizes,achieving an overall accuracy of 95.7%.This represents a 4.5%improvement compared with the PointNet network and a 2.5%enhancement over mean intersection over *** conclusion,this study substantially augments the human feature segmentation capabilities,facilitating effective collaboration with bath scrubbing robots for caregiving tasks,thereby possessing significant engineering application value.

关键词： 3D point cloud Human model LiDAR Semantic segmentation

CAT: A Simple yet Effective Cross-Attention Transformer for One-Shot Object Detection

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Journal of Computer Science & Technology 2024年第2期39卷 460-471页

作者：林蔚东邓玉岩高扬王宁刘凌峤张磊王鹏 School of Computer Science Northwestern Polytechnical UniversityXi’an710000China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean big data Application Technology Northwestern Polytechnical UniversityXi'an710000China School of Computer Science The University of AdelaideAdelaideSA 0115Australia

Given a query patch from a novel class,one-shot object detection aims to detect all instances of this class in a target image through the semantic similarity ***,due to the extremely limited guidance in the novel class as well as the unseen appearance difference between the query and target instances,it is difficult to appropriately exploit their semantic similarity and generalize *** mitigate this problem,we present a universal Cross-Attention Transformer(CAT)module for accurate and efficient semantic similarity comparison in one-shot object *** proposed CAT utilizes the transformer mechanism to comprehensively capture bi-directional correspondence between any paired pixels from the query and the target image,which empowers us to sufficiently exploit their semantic characteristics for accurate similarity *** addition,the proposed CAT enables feature dimensionality compression for inference speedup without performance *** experiments on three object detection datasets MS-COCO,PASCAL VOC and FSOD under the one-shot setting demonstrate the effectiveness and efficiency of our model,e.g.,it surpasses CoAE,a major baseline in this task,by 1.0%in average precision(AP)on MS-COCO and runs nearly 2.5 times faster.

关键词： one-shot object detection Transformer attention mechanism