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Robust Watermarking of Screen-Photography Based on JND

computers, Materials & Continua 2022年第6期71卷 4819-4833页

作者： Siyu Gu JinHan Xingming Sun Yi Cao Nanjing University of Information Science&Technology Nanjing210044China Engineering Research Center of Digital Forensics Ministry of EducationNanjing201144China Department of Electrical and Computer Engineering University of Windsor401 Sunset AvenueWindsorONN9B 3P4Canada

With the popularity of smartphones,it is often easy to maliciously leak important information by taking pictures of the *** watermarking that can resist screen photography can achieve the protection of *** the screen photo process can cause some irreversible distortion,the currently available screen photo watermarks do not consider the image content well and the visual quality is not very ***,this paper proposes a new screen-photography robust *** terms of embedding region selection,the intensity-based Scale-invariant feature transform(SIFT)algorithm used for the construction of feature regions based on the density of feature points,which can make it more focused on the key content of the image;in terms of embedding strength,the Just noticeable difference(JND)model is applied to limit the intensity of the watermark embedding according to the luminance and texture of the picture to balance robustness and invisibility;after embedding watermark,the coefficients in the neighborhood are again adjusted with optimal constraints to improve the accuracy of watermark *** experiments,it is shown that the method we proposed can improve the correct rate of watermark extraction,the quality of the visual aspect of the watermarked picture is also improved.

关键词： Screen photography robust watermarking SIFT JND

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Non-invasive estimation of the powder size distribution from a single speckle image

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Light(science & Applications) 2024年第10期13卷 2221-2230页

作者： Qihang Zhang Ajinkya Pandit Zhiguang Liu Zhen Guo Shashank Muddu Yi Wei Deborah Pereg Neda Nazemifard Charles Papageorgiou Yihui Yang Wenlong Tang Richard D.Braatz Allan S.Myerson George Barbastathis Department of Electrical Engineering and Computer Science Massachusetts Institute of TechnologyCambridgeMA 02139USA Singapore-MIT Alliance for Research and Technology(SMART)Centre Singapore 117543Singapore Department of Chemical Engineering Massachusetts Institute of TechnologyCambridgeMA 02139USA Department of Mechanical Engineering Massachusetts Institute of TechnologyCambridgeMA 02139USA Process Chemistry Development Takeda Pharmaceuticals International Co40 Landsdowne StCambridgeMA 02139USA ShinrAI Center for AI/ML Data Sciences InstitutesTakeda Pharmaceuticals International Co650 E Kendall StCambridgeMA 02142USA Present address:Department of Precision Instruments Tsinghua UniversityBeijing 100084China

Non-invasive characterization of powders may take one of two approaches:imaging and counting individual particles;or relying on scattered light to estimate the particle size distribution(PSD)of the *** former approach runs into practical difficulties,as the system must conform to the working distance and other restrictions of the imaging *** latter approach requires an inverse map from the speckle autocorrelation to the particle *** principle relies on the pupil function determining the basic sidelobe shape,whereas the particle size spread modulates the sidelobe *** recently showed that it is feasible to invert the speckle autocorrelation and obtain the PSD using a neural network,trained efficiently through a physics-informed semi-generative *** this work,we eliminate one of the most time-consuming steps of our previous method by engineering the pupil *** judiciously blocking portions of the pupil,we sacrifice some photons but in return we achieve much enhanced sidelobes and,hence,higher sensitivity to the change of the size *** result is a 60×reduction in total acquisition and processing time,or 0.25 seconds per frame in our *** real-time operation in our system is not only more appealing toward rapid industrial adoption,it also paves the way for quantitative characterization of complex spatial or temporal dynamics in drying,blending,and other chemical and pharmaceutical manufacturing processes.

关键词： speckle size distribution

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KGNet: Knowledge-Guided Networks for Category-Level 6D Object Pose and Size Estimation

KGNet: Knowledge-Guided Networks for Category-Level 6D Objec...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Qiwei Meng Jason Gu Shiqiang Zhu Jianfeng Liao Tianlei Jin Fangtai Guo Wen Wang Wei Song Zhejiang Lab Research Center for Intelligent Robotics Research Institute of Interdis-ciplinary Innovation Hangzhou China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou China Department of Electrical and Computer Engineering Dalhousie University Halifax NS Canada

Despite the giant leap made in object 6D pose estimation and robotic grasping under structured scenarios, most approaches depend heavily on the exact CAD models of target objects beforehand, thereby limiting their wide applications. To address this, we propose a novel knowledge-guided network - KGNet to estimate the pose and size of category-level unseen objects. This network includes three primary innovations: knowledge-guided categorical model generation, pointwise deformation probability matrix and synergetic RGBD feature fusion, with the former two leveraging categorical object knowledge for unseen object reconstruction and the latter one facilitating pose-sensitive feature extraction. Exten-sive experiments on CAMERA25 and REAL275 verify their effectiveness, and KGNet achieves the SOTA performance on these two acknowledged benchmarks. Additionally, a real-world robotic grasping experiment is conducted, and its results further qualitatively prove the practicability and robustness of KGNet.

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Nonlinearity of optoacoustic signals and a new contrast mechanism for imaging

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光：科学与应用（英文版） 2025年第5期14卷 1420-1432页

作者： Jaber Malekzadeh-Najafabadi Jaya Prakash Daniel Razansky Jorge Ripoll Vipul Gujrati Vasilis Ntziachristos Biological Imaging Central Institute for Translational Cancer Research(TranslaTUM)School of Medicine and Health & School of ComputationInformation and TechnologyTechnical University of MunichMunichGermany Institute of Biological and Medical Imaging Bioengineering CenterHelmholtz Zentrum MünchenNeuherbergGermany Institute for Biomedical Engineering Department of Information Technology and Electrical EngineeringETH ZurichZurichSwitzerland Biological Imaging Central Institute for Translational Cancer Research(TranslaTUM)School of Medicine and Health & School of ComputationInformation and TechnologyTechnical University of MunichMunichGermany Institute of Biological and Medical Imaging Bioengineering CenterHelmholtz Zentrum MünchenNeuherbergGermany Department of Instrumentation and Applied Physics Indian Institute of ScienceBengaluruIndia Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology Faculty of MedicineUniversity of ZurichZurichSwitzerland Institute for Biomedical Engineering Department of Information Technology and Electrical EngineeringETH ZurichZurichSwitzerland Department of Bioengineering and Aerospace Engineering Universidad Carlos Ⅲ de MadridMadridSpain Biological Imaging Central Institute for Translational Cancer Research(TranslaTUM)School of Medicine and Health & School of ComputationInformation and TechnologyTechnical University of MunichMunichGermany Institute of Biological and Medical Imaging Bioengineering CenterHelmholtz Zentrum MünchenNeuherbergGermany Biological Imaging Central Institute for Translational Cancer Research(TranslaTUM)School of Medicine and Health & School of ComputationInformation and TechnologyTechnical University of MunichMunichGermany Institute of Biological and Medical Imaging Bioengineering CenterHelmholtz Zentrum MünchenNeuherbergGermany Munich Institute of Robotics and Machine Intelligence(MIRMI) Technical University of MunichMunichGermany

Optoacoustic signals behave nonlinearly at light fluences above a few mJ/cm2,which may affect the interpretation and quantification of *** has been proposed that optoacoustic nonlinearity arises from the heat-induced formation of nanobubbles or changes in local thermo-physical ***,such explanations are only valid at much higher fluences than typically used in biomedical optoacoustic imaging(＞20 mJ/cm2)or in the presence of materials with high absorption coefficients such as gold *** propose herein that electromagnetic permittivity changes in response to photon absorption are major source of optoacoustic signal nonlinearity at low *** provide theoretical and experimental evidence that supports this postulation and show that optoacoustic pressure responses due to permittivity changes,which are function of thermally excited third-order nonlinear susceptibility,can explain the nonlinear behavior of the optoacoustic *** different materials exhibit different thermally excited third-order nonlinear susceptibility,this property could function as a new contrast mechanism that can identify the sensitivity of a substance's dielectric constant to photon-induced temperature ***,we propose an imaging method based on nonlinear optoacoustic signals that exploits this newly identified contrast *** findings may have far-reaching implications for improving the accuracy of optoacoustics and utilizing the proposed new contrast mechanism would advance our understanding of cellular and tissue functionality.

关键词： mechanism contrast imaging nonlinearity optoacoustic signals

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A Systematic Literature Review on Task Allocation and Performance Management Techniques in Cloud Data center

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computer Systems science & engineering 2024年第3期48卷 571-608页

作者： Nidhika Chauhan Navneet Kaur Kamaljit Singh Saini Sahil Verma Abdulatif Alabdulatif Ruba Abu Khurma Maribel Garcia-Arenas Pedro A.Castillo University Institute of Computing Chandigarh UniversityPunjab143001India Department of Computer Science and Engineering Chandigarh UniversityPunjab143001India Department of Computer Science and Engineering Uttaranchal UniversityUttarakhand248007India Department of Computer Science College of Computer Qassim UniversityBuraydah52571Saudi Arabia MEU Research Unit Faculty of Information TechnologyMiddle East UniversityAmman11831Jordan Department of Computer Engineering Automatics and RoboticsUniversity of GranadaGranada18071Spain Applied Science Research Center Applied Science Private UniversityAmman11931Jordan

As cloud computing usage grows,cloud data centers play an increasingly important *** maximize resource utilization,ensure service quality,and enhance system performance,it is crucial to allocate tasks and manage performance *** purpose of this study is to provide an extensive analysis of task allocation and performance management techniques employed in cloud data *** aim is to systematically categorize and organize previous research by identifying the cloud computing methodologies,categories,and gaps.A literature review was conducted,which included the analysis of 463 task allocations and 480 performance management *** review revealed three task allocation research topics and seven performance management *** allocation research areas are resource allocation,load-Balancing,and *** management includes monitoring and control,power and energy management,resource utilization optimization,quality of service management,fault management,virtual machine management,and network *** study proposes new techniques to enhance cloud computing work allocation and performance ***-comings in each approach can guide future *** research’s findings on cloud data center task allocation and performance management can assist academics,practitioners,and cloud service providers in optimizing their systems for dependability,cost-effectiveness,and *** methodologies can steer future research to fill gaps in the literature.

关键词： Cloud computing data centre task allocation performance management resource utilization

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Encrypted Domain Secret Medical-Image Sharing with Secure Outsourcing Computation in IoT Environment

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IEEE Internet of Things Journal 2024年第2期11卷 2382-2393页

作者： Huang, Jingwang Cui, Qi Zhou, Zhili Yu, Keping Yang, Ching-Nung Choo, Kim-Kwang Raymond Institute of Artificial Intelligence and Blockchain Guangzhou University Guangzhou510006 China Nanjing University Information Science and Technology Engineering Research Center of Digital Forensics Ministry of Education Nanjing210044 China Nanyang Technological University School of Electrical and Electronic Engineering Jurong West639798 Singapore Guangzhou University Institute of Artificial Intelligence and Blockchain Guangzhou510006 China Hosei University Graduate School of Science and Engineering Tokyo184-8584 Japan National Dong Hwa University Department of Computer Science and Information Engineering Hualien974301 Taiwan The University of Texas at San Antonio Department of Information Systems and Cyber Security San AntonioTX78249 United States

In existing secret medical-image sharing (SMIS) schemes, to protect and manage secret medical-images (SMIs), the sharing and recovery of each SMI are implemented by local servers of medical institutions. However, since a lot of SMIs are produced by personal smart terminal devices in Internet of Things (IoT) environment, directly implementing the sharing and recovery processes will cause excessive communication and computing burden for those local servers, which makes the existing SMIS schemes not suitable for IoT environment. To address the above issue, we propose an encrypted domain SMIS (Enc-SMIS) scheme with secure outsourcing computation for protecting and managing medical images in IoT environment. In the proposed scheme, the medical images are first encrypted using fully homomorphic encryption (FHE) and then outsourced to a cloud server for generating a set of image shares. Subsequently, these shares are stored separately in different local servers of medical institutions. Furthermore, the recovery process is also outsourced to the cloud server when doctors need to observe the patients' medical images. Compared with the existing SMIS schemes, the proposed Enc-SMIS scheme alleviates the computing and communication burden on local servers significantly with secure outsourcing computation in the semi-honest model, and thus supports the storage and management of medical images well in IoT environment. © 2014 IEEE.

关键词： Internet of things

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NCU-IISR/AS-GIS: Using BERTScore and Snippet Score to Improve the Performance of Pretrained Language Model in BioASQ 10b Phase B

NCU-IISR/AS-GIS: Using BERTScore and Snippet Score to Improv...

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2022 Conference and Labs of the Evaluation Forum, CLEF 2022

作者： Ting, Hao-Hsuan Zhang, Yu Han, Jen-Chieh Tsai, Richard Tzong-Han Interdisciplinary Program of Electrical Engineering and Computer Science National Central University Taiwan Department of Computer Science and Information Engineering National Central University Taiwan IoX Center National Taiwan University Taiwan Research Center for Humanities and Social Sciences Academia Sinica Taiwan

This paper presents our system for the BioASQ10b Phase B task. For ideal answers, we used the fine-tuned BioBERT model on the MNLI dataset to construct sentence embeddings and combined it with BERTScore to select sentences from the provided Snippets as answers. For the exact answers, we also used the BioBERT model and used the snippet scores generated from the ideal answer selection model to predict the exact answers for factoid and list questions. The exact answers of our fifth test batch ranked second place. In addition, the ideal answers we submitted achieved first place in the ROUGE score in all test batches from batch second to fifth. © 2022 Copyright for this paper by its authors.

关键词： Computational linguistics

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Multi-Path Attention Inverse Discrimination Network for Offline Signature Verification

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Intelligent Automation & Soft Computing 2023年第6期36卷 3057-3071页

作者： Xiaorui Zhang Yingying Wang Wei Sun Qi Cui Xindong Wei School of Computer and Software Nanjing University of Information Science&TechnologyNanjing210044China Wuxi Research Institute Nanjing University of Information Science&TechnologyWuxi214100China Engineering Research Center of Digital Forensics Ministry of EducationJiangsu Engineering Center of Network MonitoringNanjing210044China Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET) Nanjing University of Information Science&TechnologyNanjing210044China School of Automation Nanjing University of Information Science&TechnologyNanjing 210044China Department of Electrical and Computer Engineering University of WindsorWindsorN9B 3P4Canada School of Teacher Education Nanjing University of Information Science&TechnologyNanjing210044China

Signature verification,which is a method to distinguish the authenticity of signature images,is a biometric verification technique that can effectively reduce the risk of forged signatures in financial,legal,and other business ***,compared with ordinary images,signature images have the following characteristics:First,the strokes are slim,i.e.,there is less effective ***,the signature changes slightly with the time,place,and mood of the signer,i.e.,it has high intraclass *** challenges lead to the low accuracy of the existing methods based on convolutional neural net-works(CNN).This study proposes an end-to-end multi-path attention inverse dis-crimination network that focuses on the signature stroke parts to extract features by reversing the foreground and background of signature images,which effectively solves the problem of little effective *** solve the problem of high intraclass variability of signature images,we add multi-path attention modules between discriminative streams and inverse streams to enhance the discriminative features of signature ***,a multi-path discrimination loss function is proposed,which does not require the feature representation of the samples with the same class label to be infinitely close,as long as the gap between inter-class distance and the intra-class distance is bigger than the set classification threshold,which radically resolves the problem of high intra-class difference of signature *** addition,this loss can also spur the network to explore the detailed infor-mation on the stroke parts,such as the crossing,thickness,and connection of *** respectively tested on CEDAR,BHSig-Bengali,BHSig-Hindi,and GPDS Synthetic datasets with accuracies of 100%,96.24%,93.86%,and 83.72%,which are more accurate than existing signature verification *** is more helpful to the task of signature authentication in justice and finance.

关键词： Offline signatures biometric verification multi-path discrimination loss attention mechanisms inverse discrimination

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Modified Integrated Regulator Strategy for High Density Interleaved DC-DC Converter with Enhancement Conversion Ratio and Losses Mitigation

Modified Integrated Regulator Strategy for High Density Inte...

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Annual Conference of Industrial Electronics Society

作者： Mohsen Karimi Mohammad Farsijani Mohsin Jamil Iranian Research Institute for Electrical Engineering Academic Center for Education Culture and Research Tehran Iran Department of Electrical and Computer Engineering and Applied Science Memorial University of Newfoundland St John’s Canada Department of Electrical and Computer Engineering University of Illinois Chicago Chicago IL USA

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

The high power DC-DC converters are widely used in industrial and renewable application due to variable dc source. For this purpose, the interleaved dual cascade DCDC converter (IDCC) is the most advantageous due to its and low ripple with high boosting factor and high potential efficiency. To optimize IDCC performance, an integrated regulator ensures equal current sharing between levels, with voltage cascading to boost the output voltage. The integrated regulator technique (IRT) is designed to control all regulators at each level to maintain an optimal switching period, thereby reducing switching dissipation and decreasing ripple. Its ability to handle high voltages conversion with a consistent low ripple output and modular structure enhance performance. It has demonstrated a 1.5% current ripple and up to 94% efficiency in high-power density applications. Simulation and experimental results of a 2 kW prototype validate the IRT's performance.

关键词： Industrial electronics Renewable energy sources Regulators Prevention and mitigation Prototypes Switches DC-DC power converters Control systems Voltage control Stress

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Detection of Bleeding Events In EHR Notes Using A Graph Dynamic Autoencoder Based Riemannian Residual Neural Network 4

Detection of Bleeding Events In EHR Notes Using A Graph Dyna...

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4th IEEE International Conference on ICT in Business Industry and Government, ICTBIG 2024

作者： Niveditha, V.R. Ali, H. Mohammed Rammohan, S. Radha Rajababu, D. Maranan, R. Kaliappan, S. Sathyabama Institute of Science and Technology Department of Computer Science and Engineering Semmancheri Chennai600119 India Srm Institute of Science and Technology Department of Mechanical Engineering Ramapuram Campus Chennai89 India Hindustan University Center for Open and Digital Education Padur Chennai India Sr University Department of Electrical and Electronics Engineering Telangana Warangal506371 India Saveetha School of Engineering Simats Department of Research and Innovation Tamil Nadu Chennai602105 India Lovely Professional University Division of Research and Development Jalandhar - Delhi G.T.Road Punjab Phagwara144411 India

ISBN: (纸本)9798331518981

Identifying occurrences of abnormal bleeding based on unstructured and structured medical data, such as patient notes, vitals, and laboratory findings, is the problem of recognising bleeding events in Electronic Health Records (EHR). The problem is in accurately recognising these occurrences by analysing temporal patterns, extracting significant information, and distinguishing catastrophic bleeding occasions from typical medical fluctuations given the complexity of EHR data, which is frequently longitudinal, heterogeneous, and packed with noise. The goal is to create a Graph Dynamic Autoencoder combined with a Riemannian Residual Neural Network (GDA-RRNN) with Elk Herd optimizer (EHO) model that can identify and display bleeding incidents in electronic medical data. The EHO optimizes the hyperparameters GDA-RRNN to improve the performance of the suggested method. We extracted 300 electronic health records that contained leukaemia or bleeding diagnostic codes from the International categorization of Diseases, Tenth Revision. The electronic health record has annotations indicating whether a sentence was positive or negative for bleeding. A proposed model that can identify bleeding at the sentence and note levels was created using the annotated texts. The best-performing suggested approach achieved a sensitivity of 0.99, specificity of 0.99, and a negative prediction value of 0.99 on an equal test set of 1178 phrases. © 2024 IEEE.

关键词： Electronic health record

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