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Overview and New Opportunities for Multi-Source data Assimilation

Journal of Meteorological Research 2025年第1期39卷 1-25页

作者： Xiaolei ZOU Joint Center of Data Assimilation for Research and Application Nanjing University of Information Science&TechnologyNanjing210044China

The world witnessed an accelerated development of various types of meteorological observing technology,an evolution of numerical weather prediction(NWP)models from single atmospheric component to coupled multi-components of the earth system,as well as the multi graphics processing unit technology in computer sciences,a new era for rapidly advancing data assimilation science and technology development has *** multi-source data assimilation is important not only for NWP but also for further understanding of global and regional weather *** article firstly selectively reviews past methods of multi-source data *** opportunities are then discussed for future development of data assimilation system framework,for innovative uses of high-resolution observations,and for applications of artificial intelligence machine learning in meteorological data assimilation.

关键词： multi-source observations data assimilation innovative use of high-resolution observations

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Anti-Interference High-Speed Modulation Decoder for Quantum Key Distribution

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Chinese Physics Letters 2025年第1期42卷 34-39页

作者： Hua-Xing Xu Shao-Hua Wang Chang-Lei Wang Ping Zhang National Engineering Research Center for Public Safety Risk Perception and Control by Big Data China Academic of Electronics and Information TechnologyBeijing 100041China CETC Academy of Electronics and Information Technology Group Co. Ltd.Beijing 100041China

Quantum key distribution is increasingly transitioning toward network applications,necessitating advancements in system performance,including photonic integration for compact designs,enhanced stability against environmental disturbances,higher key rates,and improved *** this letter,we propose an orthogonal polarization exchange reflector Michelson interferometer model to address quantum channel disturbances caused by environmental *** on this model,we designed a Sagnac reflector-Michelson interferometer decoder and verified its performance through an interference *** interference fringe visibility exceeded 98%across all four coding phases at 625 *** results indicate that the decoder effectively mitigates environmental interference while supporting high-speed modulation *** addition,the proposed anti-interference decoder,which does not rely on magneto-optical devices,is well-suited for photonic integration,aligning with the development trajectory for next-generation quantum communication devices.

关键词： decoder interferometer polarization

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kProtoClust:Towards Adaptive k-Prototype Clustering without Known k

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Computers, Materials & Continua 2025年第3期82卷 4949-4976页

作者： Yuan Ping Huina Li Chun Guo Bin Hao School of Information Engineering Xuchang UniversityXuchang461000China Henan Province Engineering Technology Research Center of Big Data Security andApplications Xuchang461000China College of Computer Science and Technology Guizhou UniversityGuiyang550025China Here Data Technology Shenzhen518000China

Towards optimal k-prototype discovery,k-means-like algorithms give us inspirations of central samples collection,yet the unstable seed samples selection,the hypothesis of a circle-like pattern,and the unknown K are still challenges,particularly for non-predetermined data *** propose an adaptive k-prototype clustering method(kProtoClust)which launches cluster exploration with a sketchy division of K clusters and finds evidence for splitting and *** behalf of a group of data samples,support vectors and outliers from the perspective of support vector data description are not the appropriate candidates for prototypes,while inner samples become the first candidates for instability reduction of *** from the representation of samples in traditional,we extend sample selection by encouraging fictitious samples to emphasize the representativeness of *** get out of the circle-like pattern limitation,we introduce a convex decomposition-based strategy of one-cluster-multiple-prototypes in which convex hulls of varying sizes are prototypes,and accurate connection analysis makes the support of arbitrary cluster shapes *** by geometry,the three presented strategies make kProtoClust bypassing the K dependence well with the global and local position relationship analysis for data *** results on twelve datasets of irregular cluster shape or high dimension suggest that kProtoClust handles arbitrary cluster shapes with prominent accuracy even without the prior knowledge K.

关键词： Prototype finding convex hull support vector data description geometrical information

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TIPS:Tailored information Extraction in Public Security Using Domain-Enhanced Large Language Model

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Computers, Materials & Continua 2025年第5期83卷 2555-2572页

作者： Yue Liu Qinglang Guo Chunyao Yang Yong Liao School of Cyber Science and Technology University of Science and Technology of ChinaHefei230026China National Engineering Research Center for Public Safety Risk Perception and Control by Big Data China Academy of Electronics and Information TechnologyBeijing100041China

Processing police incident data in public security involves complex natural language processing(NLP)tasks,including information *** data contains extensive entity information—such as people,locations,and events—while also involving reasoning tasks like personnel classification,relationship judgment,and implicit ***,utilizing models for extracting information from police incident data poses a significant challenge—data scarcity,which limits the effectiveness of traditional rule-based and machine-learning *** address these,we propose *** collaboration with public security experts,we used de-identified police incident data to create templates that enable large language models(LLMs)to populate data slots and generate simulated data,enhancing data density and *** then designed schemas to efficiently manage complex extraction and reasoning tasks,constructing a high-quality dataset and fine-tuning multiple open-source *** showed that the fine-tuned ChatGLM-4-9B model achieved an F1 score of 87.14%,nearly 30%higher than the base model,significantly reducing error *** corrections further improved performance by 9.39%.This study demonstrates that combining largescale pre-trained models with limited high-quality domain-specific data can greatly enhance information extraction in low-resource environments,offering a new approach for intelligent public security applications.

关键词： Public security information extraction large language model prompt engineering

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A Network Security Situation Prediction Model Enhanced by Multi Head Attention Mechanism

Informatica (Slovenia)

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Informatica (Slovenia) 2025年第18期49卷 143-156页

作者： Chen, Jian Bian, Huanqiang Liang, Hao Laboratory and Information Technology Center Ningbo University of Finance & Economics Ningbo315175 China Ningbo City College of Vocational Technology Ningbo315175 China Big Data Division Ningbo University of Technology Ningbo315175 China

The Internet has grown as a result of information technology advancements, and cybercrime is becoming more and more common. To improve the network defense against all kinds of network attacks and reduce the success rate of cyber crimes, the research innovatively proposes to use the multi-tease attention mechanism to improve the gating cycle unit, and use the multi-head attention mechanism to obtain network security feature information at different locations, so as to improve the learning characteristics of network situation prediction and realize network security situation prediction. Three layers comprised the model: the prediction layer, the transform layer, and the circular network layer. The circular network layer was responsible for dimensionality reduction of network information data. information features were extracted via the transform layer. The outcomes of the predictions were output by the prediction layer. The study's model performed better when taught in both directions, according to the data, and its accuracy could reach roughly 93.5%. The highest level of model accuracy could be reached when other parameters were fixed and the neurons in the feed-forward layer was 28. Compared with other network security situation prediction models, the proposed model could improve the prediction accuracy to around 93.5% and the precision to around 91% on the UNSW-NB15 dataset, while maintaining the F1 value of the model at around 92%. The research-designed model can accurately predict the network security situation changes, which improves the Internet's defense against attacks and maintains the normal operation of the Internet community. © 2025 Slovene Society Informatika. All rights reserved.

关键词： Prediction models

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Research and application on visualization of ocean scalar field 6

Research and application on visualization of ocean scalar fi...

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6th International Conference on Geoscience and Remote Sensing Mapping, GRSM 2024

作者： He, Long Jiang, Xiaoyi Guo, Xue Sun, Hanrui Technology Innovation Center of Marine Information MNR Tianjin300171 China National Marine Data and Information Service Tianjin300171 China

ISBN: (纸本)9781510688018

The visualization of ocean scalar field is of great importance to scientists engaged in the analysis of marine extreme weather, the delineation of ship routes and the prediction of fish populations. This paper presents a text format transformation method for gridded marine environment data, and completed visualization with the assistance of ArcGIS API for JavaScript. This visualization method realizes the lightweight architecture of the ocean scalar field display and addresses the issues previously encountered, such as the occupation of numerous server resources and the slow response speed of the system. The visualization architecture proposed in this paper enables the effective display of diverse marine environment scalar elements, including sea temperature, salinity, sea surface height, and others, within the ODINWESTPAC system. This system provides information services for marine managers and researchers. © 2025 SPIE.

关键词： Extreme weather

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A Novel Community Detection Algorithm Based on Node Propagation and Attraction

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IEEE Access 2025年 13卷 69161-69174页

作者： Fu, Lidong Xie, Xinxing Dou, Zengfa Bai, Yun Zhao, Xi Xi'an University of Science and Technology College of Computer Science and Technology Xi'an710600 China Qinghai Institute of Technology School of Computer and Information Science Xining810016 China Xi'an University School of Information Engineering Xi'an710065 China Xi'an Big Data Service Center Xi'an710007 China

High-quality community detection in complex networks typically relies on the similarity between nodes to select communities. However, when a node exhibits the same similarity with different communities, it becomes ambiguous to determining the optimal community assignment for that node, potentially leading to incorrect predictions and affecting the accuracy of community assignments for other nodes. To address this problem, this paper proposes a novel community detection algorithm based on node propagation and attraction. The algorithm first introduces a node propagation strategy, which identifies high-propagation nodes based on their connectivity and core attributes. These high-propagation nodes form the initial backbone and framework of communities, minimizing the interference of low-propagation nodes on community structure. Subsequently, an attraction definition is introduced, which starts from high-propagation nodes to select partitioning methods based on their relationships with neighboring nodes, using the attraction among these nodes facilitate community organization and propagation, aiming to enhance community quality. Finally, in the community optimization phase, the algorithm effectively improves the accuracy of partitions that result from similar attractions by considering the association degree between nodes and communities. Experimental results demonstrate that, on both synthetic and real networks, the proposed algorithm outperforms various existing community detection algorithms. © 2013 IEEE.

关键词： Optimization algorithms

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Exploration of data Classification and Grading Strategy for Power Grid Enterprises 24

Exploration of Data Classification and Grading Strategy for ...

引用

5th International Conference on Computer Science and Management technology, ICCSMT 2024

作者： Yang, Tianguang Zhang, Yu Kang, Chunting Yan, Weisi Data Consulting Business Center Beijing SGITG-Accenture Information Technology Co. Ltd. Beijing China

ISBN: (纸本)9798400709999

In order to implement the relevant requirements in laws, regulations, standards, and specifications of the People's Republic of China, through refering to practical experiences of other industries, power grid enterprises need to explore constructing a set of data classification and grading strategies that are in line with their own business development for satisfying compliance requirements. Refering to the data classification and grading methods in the national standards, based on the comprehensive consideration of business management activities and data storage conditions, this article explores the construction of enterprise data, personal information, and public data classification strategies for power grid enterprises. Based on a combination of quantitative and qualitative statistical analysis techniques, according to the national criteria for determining important and core data, the affected objects and factors are assigned values to calculate the risk value of data items, and the data items are graded based on the risk value, providing a new data grading strategy and reference for conducting data compliance management. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： data Classification Strategy

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On the Use of Remote Sensing data for Monitoring NDVI Anomalies and Correlations with Rainfall Anomalies in West Java Province, Indonesia: Addressing Sustainable Development Goal 2

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Remote Sensing in Earth Systems Sciences 2025年第2期8卷 815-833页

作者： Roswintiarti, Orbita Indriasari, Novie Rasyidy, Fadilah Halim Sari, Inggit Lolita Kustiyo Muradi, Hengki Purbantoro, Babag Indradjad, Andy Subehi, Mokhamad Research Center for Geoinformatics National Research and Innovation Agency (BRIN) Bogor Indonesia Research Center for Data Science and Information National Research and Innovation Agency (BRIN) Bogor Indonesia Research Center for Satellite Technology National Research and Innovation Agency (BRIN) Bogor Indonesia Center for Agriculture Data and Information System Ministry of Agriculture Jakarta Indonesia

Remote sensing helps us to understand the interdependence between people, the earth, and prosperity, as pointed out in the Sustainable Development Goals framework. Sustainable agriculture is one of the Sustainable Development Goals 2 of the Zero Hunger, as outlined in Target 2.4, which addresses strengthening the capacity for adaptation to drought, flooding, climate change, and other disasters. This research aimed to address the need for productive and sustainable agriculture by investigating the impact of climate, specifically rainfall, on paddy productivity. The areas of interest selected are the Karawang, Subang, and Indramayu Regencies, the most significant rice production areas in the West Java Province of Indonesia. The Reanalysis Product of Global Satellite Mapping of Precipitation (RNL GSMaP) and the Terra/Aqua Normalized Difference Vegetation Index (NDVI) data (2001–2021) were utilized as rainfall and paddy productivity indicators, respectively. We utilized 8-day NDVI anomaly datasets and rainfall rate anomaly data for analysis via canonical correlation analysis (CCA). The application of CCA showed that, in general, rainfall anomalies and NDVI anomalies had simultaneous positive correlations during the early growth stages of paddy fields. Moreover, these parameters were negatively correlated during the reproductive paddy stage. Our findings suggest that identifying the typical lag times of the relationship between rainfall and paddy productivity in West Java Province is necessary, among others, for agricultural planning and water resource management, climate adaptation and risk management, and enhancing food security. This research supports target 2.4 of SDG 2 by providing advantageous data to enhance sustainable and resilient food production systems, thereby contributing to the broader goals of Sustainable Development Goal 2. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

关键词： Canonical correlation analysis NDVI Paddy productivity Principal component analysis RNL GSMaP SDG 2

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An Entorhinal-Hippocampal Loop Model Based on Non-negative Sparse Coding

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Journal of The Institution of Engineers (India): Series B 2025年第1期106卷 113-127页

作者： Zhao, Kaixin Ren, Menghui College of Computer Science and Technology Henan Institute of Technology Xinxiang453003 China School of Electrical and Information Engineering Zhengzhou University Zhengzhou450001 China Manufacturing IoT Big Data Engineering Technology Research Center of Henan Province Xinxiang453003 China

In our study, we investigate how the brain maps environmental spaces into understandable maps through hippocampal place cells and entorhinal cortex grid cells. We uncover that the hippocampus and entorhinal cortex are not just directly connected but also engage in a sophisticated feedback loop crucial for spatial encoding during navigation. We developed an innovative network model based on this feedback mechanism, linking entorhinal inputs to hippocampal spatial encoding cells through a non-negative sparse coding, using grid cells and weak spatial cells as inputs. Our findings demonstrate that the model learns and adjusts the characteristics of spatial encoding cells, successfully learning the specific spatial selectivities of place cells even with inputs from cells carrying weaker spatial information. This highlights the critical role of feedback encoding in refining spatial representations, an indispensable component of the brain’s navigation system. Moreover, experiments comparing our model with others validate our model’s exceptional ability in generating precise spatial encodings, underscoring its superiority. This research not only deepens our understanding of the brain’s navigational mechanisms but also offers a robust computational framework for future neuroscience studies, emphasizing the intricate interplay between feedback loops and spatial encoding in the brain’s navigation system. © The Institution of Engineers (India) 2024.

关键词： Brain

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