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A two-stage multi-fidelity design optimization for K-mer-based pattern recognition (KPR) in image processing

A two-stage multi-fidelity design optimization for K-mer-bas...

ASME 2020 International Design engineering Technical Conferences and Computers and Information in engineering Conference, IDETC-CIE 2020

作者： Yao, Yu-Ta Wu, Yu-Wei Lin, Po Ting Department of Mechanical Engineering National Taiwan University of Science and Technology Taipei10607 Taiwan Graduate Institute of Biomedical Informatics Taipei Medical University Taipei11031 Taiwan Clinical Big Data Research Center Taipei Medical University Hospital Taipei11031 Taiwan Center for Cyber-Physical System Innovation National Taiwan University of Science and Technology Taipei10607 Taiwan

ISBN: (纸本)9780791884010

Pattern recognition has been widely used in various applications of image processing. It is used to extract meaningful image features from the given image samples and to build classification systems with the intelligence of human recognition. Convolutional Neural Network (CNN) [1] has been one of the most popular and widely used methods for image pattern recognition applications. However, CNN was known not to be rotation-invariant to image patterns. It usually required a larger amount of training image dataset with greater variations in positions and orientations, or additional numerical treatments of spatial transformations [2]. On the other hand, K-mer-based Pattern Recognition (KPR) [3] has been developed to apply an unique way of rotation-invariant sampling to the inspected image pattern and analyze the frequency of the captured pattern features. A classification system was then built based on the Kmer frequency for the desired pattern recognition. In this paper, a series of tests and verifications of the KPR was done. It was found that finding the appropriate design parameters of the KPR for a specific application of image pattern recognition could be costly. A two-stage multi-fidelity design optimization was utilized to improve the efficiency of finding the parameters of KPR. In each iteration of the multi-fidelity design optimization procedure, the first stage was to evaluate the accuracy and efficiency of the design parameters in the K-mer-based pattern classification based on a full set of the given images. The second stage was to find a newer set of design parameters that performed the best based on a smaller set of images, which provided a classification set with lower fidelity than the original one. As a result, the proposed strategy of the multi-fidelity design optimization was more efficient than finding the optimal design parameters based on the full set of the given images. Copyright © 2020 ASME.

关键词： Iterative methods

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A Solution-Based Tabu Search Algorithm for the Resource-Constrained Project Scheduling Problem with Step Deterioration

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Mathematical Problems in engineering 2023年第1期2023卷

作者： Dai, Huafeng Li, Lei Mao, Run Liu, Xingyue Zhou, Kun School of Mechanical Engineering Chengdu University Chengdu610105 China Technology and Equipment of Rail Transit Operation and Maintenance Key Laboratory of Sichuan Province Chengdu610031 China CNPC National Engineering Research Center for Oil & Gas Drilling Equipment Co. Ltd. Chengdu610052 China School of Information Science and Engineering Chengdu University Chengdu610105 China Key Lab. of Intelligent Manufacturing Quality Big Data Tracing and Analysis of Zhejiang Province China Jiliang University Hangzhou310018 China

This paper integrates the classical resource-constrained project scheduling problem with step deterioration and accordingly presents a solution-based tabu search (SB-TS) algorithm to solve it with challenging computations. First, we choose successor list size as the priority rule to generate the initial solution of the presented methods. Next, the corresponding solution decoding and calculation ways are defined to update the related configuration at each iteration. Compared with the state-of-the-art methods, in terms of the known datasets, the proposed SB-TS finds the optimal solution for each instance in J30 and shows strongly competitive performance in J60, J90, and J120. Then, on newly generated datasets, where the step deterioration is attached to, the comparison experimental data state that the SB-TS with high-quality solution is superior to the move-based tabu search (MB-TS) algorithm. In addition, two key components are investigated to emphasize their attributions to the proposed algorithm. © 2023 Huafeng Dai et al.

关键词： Deterioration

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RPF-Net: A multimodal model for the postoperative UISS risk stratification of non-metastatic ccRCC based on CT and whole-slide images

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Computer Methods and Programs in Biomedicine 2025年 268卷 108836-108836页

作者： Mao, Jiahui Li, Wuchao Sun, Xinhuan Fu, Bangkang He, Junjie Yan, Chongzhe Zhu, Jianguo Zhang, Zhuxue Mao, Jiahui Hong, Zhangxin Tang, Qi Liu, Zhen Li, Pinhao Zhang, Yan Wang, Rongpin Medical College Guizhou University Guiyang550025 China Department of Radiology International Exemplary Cooperation Base of Precision Imaging for Diagnosis and Treatment Guizhou Provincial People's Hospital Guiyang550002 China CETC Big Data Research Institute Co. Ltd. Guizhou550022 China National Engineering Research Center of Big Data Application to Improvement of Governance Capacity Guizhou550022 China Department of Pathology Guizhou Provincial People's Hospital Guiyang550002 China Department of Urinary Guizhou Provincial People's Hospital Guiyang550002 China Department of Pathology Affiliated Hospital of Guizhou Medical University Guiyang550002 China Department of Imaging Affiliated Hospital of Guizhou Medical University Guiyang550002 China Suzhou Institute of Biomedical Engineering and Technology Chinese Academy of Sciences Suzhou215163 China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai 200082 China

Background and objectives: Postoperative non-metastatic clear cell renal cell carcinoma (nccRCC) patients face the risk of tumor recurrence and metastasis. However, prognosis assessment for nccRCC remains time-consuming and subjective. In the current diagnostic landscape, computed tomography (CT) images provide macro-scale anatomical information, and whole-slide images (WSIs) offer micro-scale details that are inaccessible to CT imaging. To address this gap, the study proposes a multimodal approach that leverages both CT and WSI data to develop an automated model for postoperative risk stratification in nccRCC. Methods: This study proposes a multimodal model named the Radiology-Pathology Fusion Network (RPF-Net), which employs self-attention, graph-attention, and dynamic attention fusion mechanisms to integrate CT images and WSIs for classifying nccRCC patients into low-risk and intermediate-high-risk groups per the University of California, Los Angeles, Integrated Staging system (UISS) criteria. The proposed model is divided into three steps. First, the ResNet-50 and 3D ResNet-50 are used as feature extractors to respectively extract representative feature maps from WSIs and CT images. Second, a dual-branch module is designed to extract global and local features of the WSIs. Finally, a multilayer dynamic attention fusion (MDAF) module is developed to facilitate cross-modal feature interaction and predict the risk stratification results. Results: The area under the curve (AUC), accuracy, precision, and F1 Score of the RPF-Net on the internal validation set are 0.949±0.013, 0.894±0.019, 0.895±0.020, and 0.894±0.019, respectively. Furthermore, the RPF-Net shows robust generalization, achieving an AUC of 0.901 on the external validation set and 0.924 on the public dataset. Conclusions: The RPF-Net models the diagnostic process of multimodal data and shows strong generalization and excellent performance. This model may be a potential tool to facilitate clinical risk str

关键词： Non-metastatic clear cell renal cell carcinoma Computed tomography Whole-slide image UISS Multimodal model

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Generative assimilation and prediction for weather and climate

arXiv

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arXiv 2025年

作者： Yang, Shangshang Nai, Congyi Liu, Xinyan Li, Weidong Chao, Jie Wang, Jingnan Wang, Leyi Li, Xichen Chen, Xi Lu, Bo Xiao, Ziniu Boers, Niklas Yuan, Huiling Pan, Baoxiang Institute of Atmospheric Physics Chinese Academy of Sciences Beijing China School of Atmospheric Sciences Key Laboratory of Mesoscale Severe Weather Ministry of Education Nanjing University Nanjing China Earth System Modelling School of Engineering and Design Technical University of Munich Munich Germany Complexity Science Potsdam Institute for Climate Impact Research Potsdam Germany Chinese Academy of Meteorological Sciences Beijing China College of Meteorology and Oceanography National University of Defense Technology Changsha China School of Mathematical Sciences Peking University Beijing China Chongqing Research Institute of Big Data Peking University Chongqing China China Meteorological Administration Key Laboratory for Climate Prediction Studies National Climate Center Beijing China Xiong’an Institute of Meteorological Artificial Intelligence Xiong’an China

Machine learning models have shown great success in predicting weather up to two weeks ahead, outperforming process-based benchmarks [1–4]. However, existing approaches mostly focus on the prediction task, and do not incorporate the necessary data assimilation. Moreover, these models suffer from error accumulation in long roll-outs, limiting their applicability to seasonal predictions [5] or climate projections [6]. Here, we introduce Generative Assimilation and Prediction (GAP), a unified deep generative framework for assimilation and prediction of both weather and climate. By learning to quantify the probabilistic distribution of atmospheric states under observational, predictive, and external forcing constraints, GAP excels in a broad range of weather-climate related tasks, including data assimilation, seamless prediction, and climate simulation. In particular, GAP is competitive with state-of-the-art ensemble assimilation, probabilistic weather forecast and seasonal prediction, yields stable millennial simulations, and reproduces climate variability from daily to decadal time scales. © 2025, CC BY-NC-SA.

关键词： Prediction models

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COVID-19大流行期间流感活动呈“断崖式”下降——佩戴口罩、人员流动变化及SARS-CoV-2干扰的作用

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engineering 2023年第2期21卷 195-202,M0008页

作者：韩莎莎张婷吕岩赖圣杰戴佩希郑建东杨维中周晓华冯录召 Beijing International Center for Mathematical Research Peking UniversityBeijing 100871China Harvard Medical School Harvard UniversityBostonMA 02115USA School of Population Medicine and Public Health Chinese Academy of Medical Sciences&Peking Union Medical CollegeBeijing 100730China Academy for Advanced Interdisciplinary Studies Peking UniversityBeijing 100871China WorldPop School of Geography and Environmental ScienceUniversity of SouthamptonSouthampton SO171BJUK Division for Infectious Diseases Chinese Center for Disease Control and PreventionBeijing 102206China Department of Epidemiology and Biostatistics School of Public HealthPeking UniversityBeijing 100871China National Engineering Laboratory of Big Data Analysis and Applied Technology Peking UniversityBeijing 100871China

一般情况下,每年冬季是季节性流感高发季节,但在当前2019冠状病毒病(COVID-19)大流行期间,全球季节性流感活动呈“断崖式”下降。为应对即将到来的流感季节,亟需弄清这种前所未有的流感低水平流行的原因。本文中,我们探索了一种国家特... 详细信息

一般情况下,每年冬季是季节性流感高发季节,但在当前2019冠状病毒病(COVID-19)大流行期间,全球季节性流感活动呈“断崖式”下降。为应对即将到来的流感季节,亟需弄清这种前所未有的流感低水平流行的原因。本文中,我们探索了一种国家特异性推理模型,利用该模型估计中国、英国和美国这三个国家中佩戴口罩、人员流动变化(国际和国内)以及严重急性呼吸综合征冠状病毒2型(SARS-CoV-2)干扰的影响。结果发现,在这些地区增加一周佩戴口罩的干预措施,流感活动可减少11.3%~35.2%。实施一周的限制人员流动措施对国际(1.7%~6.5%)和国内社区(1.6%~2.8%)的影响较小。2020年至2021年,仅佩戴口罩这一项干预措施就可使阳性率下降13.3%至19.8%。仅人员流动变化可使阳性率降低5.2%至14.0%,其中79.8%~98.2%归因于国际旅行限制。SARS-CoV-2干扰仅在2019年至2020年具有统计学显著效应。中国北方地区及英国的阳性百分比分别降低7.6%(2.4~14.4)和10.2%(7.2~13.6)。探索所得出的结果对了解非药物干预措施和其他呼吸系统疾病背景下的流感演变有一定意义,有助于制定卫生政策,并可为公共卫生措施的个性化设计提供信息。

关键词：卫生政策非药物干预呼吸系统疾病流行期间季节性流感流动变化个性化设计模型估计

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Towards Lightweight Serverless Computing via Unikernel as a Function

Towards Lightweight Serverless Computing via Unikernel as a ...

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International Workshop on Quality of Service

作者： Bo Tan Haikun Liu Jia Rao Xiaofei Liao Hai Jin Yu Zhang National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab/Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China The University of Texas at Arlington

ISBN: (数字)9781728168876

ISBN: (纸本)9781728168883

Serverless computing, also known as “Function as a Service (FaaS)”, is emerging as an event-driven paradigm of cloud computing. In the FaaS model, applications are programmed in the form of functions that are executed and managed separately. Functions are triggered by cloud users and are provisioned dynamically through containers or virtual machines (VMs). The startup delays of containers or VMs usually lead to rather high latency of response to cloud users. Moreover, the communication between different functions generally relies on virtual net devices or shared memory, and may cause extremely high performance overhead. In this paper, we propose Unikernel-as-a-Function (UaaF), a much more lightweight approach to serverless computing. Applications are abstracted as a combination of different functions, and each function are built as an unikernel in which the function is linked with a specified minimum-sized library operating system (LibOS). UaaF offers extremely low startup latency to execute functions, and an efficient communication model to speed up inter-functions interactions. We exploit an new hardware technique (namely VMFUNC) to invoke functions in other unikernels seamlessly (mostly like inter-process communications), without suffering performance penalty of VM Exits. We implement our proof-of-concept prototype based on KVM and deploy UaaF in three unikernels (MirageOS, IncludeOS, and Solo5). Experimental results show that U aaF can significantly reduce the startup latency and memory usage of serverless cloud applications. Moreover, the VMFUNC-based communication model can also significantly improve the performance of function invocations between different unikernels.

关键词： Cloud computing FAA Libraries Containers Task analysis Computer architecture Virtual machine monitors

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Partitioning large-scale property graph for efficient distributed query processing 21

Partitioning large-scale property graph for efficient distri...

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21st IEEE International Conference on High Performance Computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on data Science and systems, HPCC/SmartCity/DSS 2019

作者： Pang, Haohan Gan, Peng Yuan, Pingpeng Jin, Hai Hua, Qiangsheng National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab. Clusters and Grid Computing Lab. School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9781728120584

Recently, many communities have published their domain knowledge in the form of graphs. A significant trend is that the relations between pairs of nodes in the graph have become so complex that these data can be treated as property graphs. Complex properties imply semantic constraints which can distinguish elements of property graph into different semantic-related aspects. If the property graph can be partitioned according to these aspects, cross-partition communication would be reduced when evaluating SPARQL queries, for the reason that a query can often be evaluated in a single aspect. Conventional graph partition methods, however, pay little attention to semantic constraints in property graphs. To solve this problem, we propose a new property graph partition method for query optimization. First, we propose the property semantic reachable path as basic partition element, with which to capture the semantic-related aspects in a property graph. Second, to combine paths into partitions, we develop a space-efficient algorithm which merges vertices rather than entire paths. Extensive experiments over representative property graph data confirm the effectiveness of our semantic awareness approach. The performance of our approach is comparable with leading competitors, in terms of load balance, data redundancy, and network overhead. © 2019 IEEE.

关键词： Semantics

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Comparative Analysis of Two Angle Normalization Approaches for SAR Backscatter: Simulation and Satellite Observation-Based Evaluation in Soil Moisture Retrieval

Comparative Analysis of Two Angle Normalization Approaches f...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Dong Fan Zhen Wang Fuli Luo Jiliu Hu Junxuan Liu Bo-Hui Tang Faculty of Land Resources Engineering Kunming University of Science and Technology Kunming China Department of Education of Yunnan Province Key Laboratory of Plateau Remote Sensing Kunming China National Geomatics Center of China Beijing China College of Civil Engineering Southwest Forestry University Kunming China State Key Lab of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

Local incidence angle (LIA) normalization is an important method to improve the accuracy of active microwave remote sensing-based soil moisture retrieval in mountainous areas. In this study, the differences between two commonly used synthetic aperture radar (SAR) backscatter LIA normalization methods, cosine-based and liner-based, were compared using simulated and Sentinel-1 SAR data. The influence of two backscatter normalization methods on soil moisture retrieval in the dual-temporal dual-channel (DTDC) algorithm is analyzed. The results show that the difference between the normalized backscatter by the two methods is less than 0.3 dB in most cases. Despite the simplicity of the methods, both angle normalization techniques can rectify variations in backscattering induced by the LIA effect and improve the accuracy of soil moisture retrieval.

关键词： Accuracy Smoothing methods Satellites Soil moisture Sentinel-1 Microwave theory and techniques Synthetic aperture radar

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Future-proofing cities against negative city mobility and public health impacts of impending natural hazards: a system dynamics modelling study

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The Lancet Planetary Health 2025年第3期9卷 e207-e218页

作者： Garcia, Leandro Hafezi, Mehdi Lima, Larissa Millett, Christopher Thompson, Jason Wang, Ruoyu Akaraci, Selin Goel, Rahul Reis, Rodrigo Nice, Kerry A Zapata-Diomedi, Belen Hallal, Pedro C Moro, Esteban Amoako, Clifford Hunter, Ruth F Centre for Public Health Queen's University Belfast Belfast United Kingdom Physical Activity Epidemiology Group University of São Paulo São Paulo Brazil Complex Systems Governance Group Faculty of Engineering and Applied Sciences Cranfield University Cranfield United Kingdom Public Health Policy Evaluation Unit School of Public Health Imperial College London London United Kingdom NOVA National School of Public Health Public Health Research Centre Comprehensive Health Research Center NOVA University Lisbon Lisbon Portugal Instituto de Estudos para Políticas de Saúde São Paulo Brazil Transport Health and Urban Systems Research Lab Faculty of Architecture Building and Planning University of Melbourne Melbourne VIC Australia Institute of Public Health and Wellbeing University of Essex Essex United Kingdom Transportation Research and Injury Prevention Centre Indian Institute of Technology Delhi New Delhi India People Health & Place Research Unit Prevention Research Center School of Public Health Washington University in St. Louis St Louis MO United States Healthy Liveable Cities Lab Centre for Urban Research RMIT University Melbourne VIC Australia Department of Health and Kinesiology University of Illinois Urbana–Champaign IL United States Connection Science Institute for Data Science and Society MIT Cambridge MA United States Department of Mathematics and GISC Universidad Carlos III de Madrid Leganes Spain Department of Planning College of Art and Built Environment Kwame Nkrumah University of Science and Technology Kumasi Ghana

Background: The world faces increasing risk from more frequent and larger scale natural hazards, including infectious disease outbreaks (IDOs) and climate change-related extreme weather events (EWEs). These natural hazards are expected to have adverse mobility and public health impacts, with people living in cities especially vulnerable. Little is known about how transport systems can be optimally designed to make cities more resilient to these hazards. Our aim was to investigate how cities’ transport systems, and their resulting mobility patterns, affect their capabilities to mitigate mobility and health impacts of future large-scale IDOs and EWEs. Methods: system dynamics modelling was used to investigate how different city mobility scenarios can affect the health and mobility impacts of four plausible future IDO and EWE (flooding) shocks in three cities: Belfast, UK;Belo Horizonte, Brazil;and Delhi, India. Three city mobility scenarios with incremental degrees of modal shift towards active travel (private motor vehicle volume reduced to 50% and 20% of total road trip volume in vision 1 and 2, and motor vehicle volume [including buses] reduced to 20% of total road trip volume in vision 3) were tested. For each city and each IDO and EWE shock, we estimated the percentage of deaths prevented in visions 1, 2, and 3, relative to the reference scenario, as well as changes in mode share over time. Findings: In all scenarios, all cities showed reduced susceptibility to flooding, with 4–50% of deaths potentially prevented, depending on case city, city mobility, and EWE scenario. The more ambitious the transition towards healthier city mobility patterns, the greater the resilience against flooding. Only vision 3 (the most ambitious transition) showed reduced vulnerability to IDOs, with 6–19% of deaths potentially prevented. Evolution of mode shares varied greatly across cities and mobility scenarios under the IDO shocks. Interpretation: Our results emphasise the importance

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In-situ synthesized SiC/TiC/SiTiOC hybrid nanofiber mats for broad-range temperature microwave absorption

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Science China Technological Sciences 2025年第6期 183-196页

作者： Yashan HUO Yuetong QIAN Minshan ZHAO Lei ZHANG Yujia TAN Zhihui HE Peng MIAO Fuchun ZHANG Wei CUI Renchao CHE School of Physics and Electronic Information Yan'an University Shaanxi Key Laboratory of Intelligent Processing for Big Energy Data Laboratory of Advanced Materials Shanghai Key Lab of Molecular Catalysis and Innovative Materials Academy for Engineering &Technology Advanced Coatings Research Center of Ministry of Education of China Fudan University School of Materials and Chemical Engineering Xi'an Technological University School of Materials Science & Engineering Tongji University College of Physics Donghua University

Efficient, temperature-insensitive electromagnetic attenuation materials are critical for high microwave absorption at high temperatures. This study presents SiC/TiC/SiTiOC hybrid nanofiber mats constructed using an in-situ synthesis method;these mats incorporate SiC/TiC as the microwave loss unit and SiTiOC as the antioxidant unit, offering an innovative approach to high-temperature microwave absorption. The introduction of high-conductivity TiC not only optimizes the dielectric constant and impedance matching of the material but also enhances its thermal cycling stability. This design ensures steady electromagnetic attenuation, enabling the hybrid nanofiber mats to maintain robust absorption performance in the X-band, even at high temperatures. At 873 K, the material demonstrates an effective absorption bandwidth of 3.6 GHz and a minimum reflection loss of-45.55 dB. Compared to single-system absorbers, such as SiC/C nanofiber materials, with a single system, the multicomponent SiC/TiC/SiTiOC hybrid nanofiber mats deliver reliable absorption performance in the temperature range of 293–873 K. This study confirms that highly conductive titanium-based ceramic materials used for dielectric property regulation effectively address the challenges of poor temperature stability and limited reusability in high-temperature carbon-ceramic absorbing materials, providing valuable insights and guidance for designing efficient microwave absorbers that can operate across a wide temperature range.

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