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A Practical Approach to Constructing a Geological Knowledge Graph:A Case Study of Mineral Exploration Data

Journal of Earth Science 2023年第5期34卷 1374-1389页

作者： Qinjun Qiu Bin Wang Kai Ma Hairong Lü Liufeng Tao Zhong Xie Collaborative Innovation Center of Geo-Information Technology for Smart Central Plains Zhengzhou 450046China Key Laboratory of Spatiotemporal Perception and Intelligent Processing Ministry of Natural ResourcesZhengzhou 450046China Key Laboratory of Geological Survey and Evaluation of Ministry of Education China University of GeosciencesWuhan 430074China Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering China Three Gorges UniversityYichang 443002China College of Computer and Information Technology China Three Gorges UniversityYichang 443002China Department of Automation Tsinghua UniversityBeijing 100084China

Open data initiatives have promoted governmental agencies and scientific organizations to publish data online for *** of geoscience focuses on processing georeferenced quantitative data(e.g.,rock parameters,geochemical tests,geophysical surveys and satellite imagery)for discovering new *** knowledge is the cognitive result of human knowledge of the spatial distribution,evolution and interaction patterns of geological objects or *** graphs(KGs)can formalize unstructured knowledge into structured form and have been used in supporting decision-making *** this paper,we propose a novel framework that can extract the geological knowledge graph(GKG)from public reports relating to a modelling *** on the analysis of basic questions answered by geology,we summarize and abstract geological knowledge elements and then explore a geological knowledge representation model with three levels of“geological conceptsgeological entities-geological relations”to describe semantic units of geological knowledge and their logic ***,based on the characteristics of mineral resource reports,the geological knowledge representation model oriented to“object relationships”and the hierarchical geological knowledge representation model oriented to“process relationships”are proposed with reference to the commonly used geological knowledge graph *** research in this paper can provide some implications for the formalization and structured representation of geological knowledge graphs.

关键词： mineral resource report geological knowledge knowledge graph ontology hierarchical knowledge representation model

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Development prospects of metal-based two-dimensional nanomaterials in lithium-sulfur batteries

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Chinese Chemical Letters 2023年第1期34卷 102-113页

作者： Yuxue Mo Liling Liao Dongyang Li Rongwu Pan Yanhong Deng Yanliang Tan Haiqing Zhou College of Physics and Electronic Engineering Hengyang Normal UniversityHengyang 421002China Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Key Laboratory for Matter Microstructure and Function of Hunan ProvinceDepartment of Physics and Synergetic Innovation Center for Quantum Effects and ApplicationsHunan Normal UniversityChangsha 410081China Hunan Joint International Laboratory of Advanced Materials and Technology for Clean Energy Changsha 410082China Hunan Shengli High-tech Energy Technology Co. Ltd.Yongzhou 425000China Hunan Provincial Key Laboratory of Intelligent Information Processing and Application Hengyang 421002China

A lithium-sulfur(Li-S)system is an important candidate for future lithium-ion system due to its low cost and high specific theoretical capacity(1675 m Ah/g,2600 Wh/kg),which is greatly hindered by the poor conductivity of sulfur,large volume change and dissolution of lithium ***-dimensional(2D)materials with monolayers or few-layers usually have peculiar structures and physical/chemical properties,which can resolve the critical issues in Li-S ***,the metal-based 2D nanomaterials,including ferrum,cobalt or other metal-based composites with various anions,can provide high conductivity,large surface area and abundant reaction sites for restraining the diffusion for lithium *** this mini-review,we will present an overview of recent developments on metal-based 2D nanomaterials with various anions as the electrode materials for Li-S *** the main bottleneck for the Li-S system is the shuttle of polysulfides,emphasis is placed on the structure and components,physical/chemical interaction and interaction mechanisms of the 2D ***,the challenges and prospects of metal-based 2D nanomaterials for Li-S batteries are discussed and proposed.

关键词： Lithium-sulfur battery Two-dimensional materials Cathode materials Anode materials Anode protection

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NCCNet: Arbitrary Neural Style Transfer with Multi-channel Conversion 12th

NCCNet: Arbitrary Neural Style Transfer with Multi-channel ...

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12th International Conference on Image and Graphics, ICIG 2023

作者： Xiang, Jin Zhao, Huihuang Lin, Mugang Liu, Qingyun College of Computer Science and Technology Hengyang Normal University Hengyang421002 China Hunan Provincial Key Laboratory of Intelligent Information Processing and Application Hengyang421002 China

ISBN: (纸本)9783031463136

Arbitrary style transfer aims to create a novel image from a content image and a style image, stylizing the content image with the style of the style image. However, recent algorithms are prone to unnatural output due to focusing on the statistical distribution of deep features and ignoring the relationship between channels in feature maps. In this paper, we devise a novel Arbitrary Neural Style Transfer Network called NCCNet, which is useful for artistic style transfer. Specifically, NCCNet creates good visual effects by fusing different layers of textures. Moreover, we design an Effective Channel Conversion Modules (ECCM) which uses a multi-channel matrix to rearrange style feature maps to the appropriate range by analyzing the relationship between channels. Then, we can obtain a covariance based on the rearranged style feature map. At the same time, we design a decoder named Self-Adaptive Decoder (SA-Decoder) that conforms to our algorithm. Moreover, we apply our algorithm to the video style transfer and get good results. Qualitative and quantitative evaluations demonstrate that NCCNet performs well in arbitrary video and image style transfer tasks. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Textures

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Learning to Learn Transferable Generative Attack for Person Re-Identification

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IEEE Transactions on Image processing 2025年 PP卷 PP页

作者： Bian, Yuan Liu, Min Wang, Xueping Ma, Yunfeng Wang, Yaonan Hunan University National Engineering Research Center of Robot Visual Perception and Control Technology College of Electrical and Information Engineering Hunan Changsha China Hunan Normal University Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing College of Information Science and Engineering Hunan Changsha China

Deep learning-based person re-identification (reid) models are widely employed in surveillance systems and inevitably inherit the vulnerability of deep networks to adversarial attacks. Existing attacks merely consider cross-dataset and cross-model transferability, ignoring the cross-test capability to perturb models trained in different domains. To powerfully examine the robustness of real-world re-id models, the Meta Transferable Generative Attack (MTGA) method is proposed, which adopts meta-learning optimization to promote the generative attacker producing highly transferable adversarial examples by learning comprehensively simulated transfer-based crossmodel&dataset&test black-box meta attack tasks. Specifically, cross-model&dataset black-box attack tasks are first mimicked by selecting different re-id models and datasets for meta-train and meta-test attack processes. As different models may focus on different feature regions, the Perturbation Random Erasing module is further devised to prevent the attacker from learning to only corrupt model-specific features. To boost the attacker learning to possess cross-test transferability, the Normalization Mix strategy is introduced to imitate diverse feature embedding spaces by mixing multi-domain statistics of target models. Extensive experiments show the superiority of MTGA, especially in cross-model&dataset and cross-model&dataset&test attacks, our MTGA outperforms the SOTA methods by 20.0% and 11.3% on mean mAP drop rate, respectively. © 1992-2012 IEEE.

关键词： Generative adversarial networks

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Modality Unified Attack for Omni-Modality Person Re-Identification

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IEEE Transactions on information Forensics and Security 2025年

作者： Bian, Yuan Liu, Min Yi, Yunqi Wang, Xueping Ma, Yunfeng Wang, Yaonan Hunan University National Engineering Research Center of Robot Visual Perception and Control Technology College of Electrical and Information Engineering Hunan Changsha China Hunan Normal University Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing College of Information Science and Engineering Hunan Changsha China

Deep learning based person re-identification (re-id) models have been widely employed in surveillance systems. Recent studies have demonstrated that black-box single-modality and cross-modality re-id models are vulnerable to adversarial examples (AEs), leaving the robustness of multi-modality re-id models unexplored. Due to the lack of knowledge about the specific type of model deployed in the target black-box surveillance system, we aim to generate modality unified AEs for omni-modality (single-, cross- and multi-modality) re-id models. Specifically, we propose a novel Modality Unified Attack method to train modality-specific adversarial generators to generate AEs that effectively attack different omni-modality models. A multi-modality model is adopted as the surrogate model, wherein the features of each modality are perturbed by metric disruption loss before fusion. To collapse the common features of omnimodality models, Cross Modality Simulated Disruption approach is introduced to mimic the cross-modality feature embeddings by intentionally feeding images to non-corresponding modality-specific subnetworks of the surrogate model. Moreover, Multi Modality Collaborative Disruption strategy is devised to facilitate the attacker to comprehensively corrupt the informative content of person images by leveraging a multi modality feature collaborative metric disruption loss. Extensive experiments show that our MUA method can effectively attack the omni-modality re-id models, achieving 55.9%, 24.4%, 49.0% and 62.7% mean mAP Drop Rate, respectively. © 2005-2012 IEEE.

关键词： Modality unified attack Multi Modality Collaborative Disruption Omni-Modality re-id

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Dimension Reduction Based on Grouped Feature Selection Strategy for Fluorescence Molecular Tomography 46

Dimension Reduction Based on Grouped Feature Selection Strat...

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46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024

作者： Li, Linxin Zhang, Lizhi Zhao, Yizhe Xie, Qiong He, Xiaowei He, Xuelei Yi, Huangjian Northwest University School of Information Sciences and Technology Shaanxi Xi'an710069 China The Xi'an Key Laboratory of Radiomics and Intelligent Perception No. 1 Xuefu Avenue Shaanxi Xi'an710127 China The First Hospital of Hunan University of Chinese Medicine Hunan Changsha410007 China

ISBN: (纸本)9798350371499

Fluorescence Molecular Tomography (FMT) is an optical molecular imaging technique with high sensitivity. Multi-point excitation and multi-view measurement have improved the recovered results while also resulting in high computation and memory requirements. In this work, we proposed a grouped feature selection strategy (GFS) based on correlation and information entropy to reduce the size of the system matrix. It further reduced the computational complexity. Firstly, a similarity is constructed based on the correlation between the matrix rows. Then a group is created by the surface measurements. Secondly, information entropy is defined to measure the information contained in the surface measurement. Finally, these two measurement methods are combined with minimum redundancy and maximum relevance (mRMR) to construct the optimal subset of the original data, which completes the dimensionality reduction of the matrix. Numerical simulation experiments show that GFS outperforms the traditional principal component analysis (PCA) method in terms of reconstruction accuracy and reconstruction *** Relevance - The primary objective of this work is to enhance the reconstruction speed of FMT. Current experiments are focused on simulation experiments, while the proposed downscaling strategy will facilitate rapid clinical diagnosis and treatment decisions in the future © 2024 IEEE.

关键词： Surface measurement

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Visualization and visual analysis of cyberspace metaphors based on continuous cartogram 2

Visualization and visual analysis of cyberspace metaphors ba...

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2023 2nd International Conference on Environmental Remote Sensing and Geographic information technology, ERSGIT 2023

作者： Liu, Longhui Zhou, Yang Shi, Qunshan Hu, Xiaofei Shi, Shihao PLA Strategic Support Force Information Engineering University Institute of Geospatial Information Henan Zhengzhou450001 China Collaborative Innovation Center of Geo-Information Technology for Smart Central Plains Zhengzhou450001 China Key Laboratory of Spatiotemporal Perception and Intelligent Processing Ministry of Natural Resources Zhengzhou450001 China

ISBN: (纸本)9781510672949

Cyberspace mapping has emerged as a new and compelling area of research within the field of cartography. This paper addresses the challenge of overlapping points in cyberspace visualization, which poses difficulties for visual analysis. To tackle this issue, we propose a cyberspace metaphorical cartogram map that combines metaphorical mapping and continuous cartogram technology. Additionally, based on our method, we use our method to construct a cyberspace map using global IPv6 data from the Asia-Pacific Network information Center (APNIC) to analyze the current development pattern of the global IPv6 network. Experimental results demonstrate the effectiveness of our method in avoiding node duplication, aligning with the reading logic of geospatial maps, and providing an efficient visualization approach for data comprehension. © 2024 SPIE.

关键词： Visualization

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Semantic Maximum Relevance and Modal Alignment for Cross-Modal Retrieval 11

Semantic Maximum Relevance and Modal Alignment for Cross-Mod...

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11th International Conference on Computing and Pattern Recognition, ICCPR 2022

作者： Sun, Pingping Qiang, Baohua Liu, Zhiguang Yang, Xianyi Xi, Guangyong Liu, Weigang Chen, Ruidong Zhang, Shihao Guilin University of Electronic Technology China The 54th Research Institute of Cetc Hebei Key Laboratory of Intelligent Information Perception and Processing China

ISBN: (纸本)9781450397056

With the increasing abundance of multimedia data resources, researches on mining the relationship between different modalities to achieve refined cross-modal retrieval are gradually emerging. In this paper, we propose a novel Semantic Maximum Relevance and Modal Alignment (SMR-MA) for Cross-Modal Retrieval, which utilizes the pre-trained model with abundant image text information to extract the features of each image text, and further promotes the modal information interaction between the same semantic categories through the modal alignment module and the multi-layer perceptron with shared weights. In addition, multi-modal embedding is distributed to the normalized hypersphere, and angular edge penalty is applied between feature embedding and weight in angular space to maximize the classification boundary, thus increasing both intra-class similarity and inter-class difference. Comprehensive analysis experiments on three benchmark datasets demonstrate that the proposed method has superior performance in cross-modal retrieval tasks and is significantly superior to the state-of-the-art cross-modal retrieval methods. © 2022 ACM.

关键词： Alignment

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Lightweight 6-bit S-boxes with DPA Resistance

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IEEE Transactions on Network Science and Engineering 2025年

作者： Yan, Liuyan Li, Lang Song, Qingling Hengyang Normal University College of Computer Science and Technology Hunan Provincial Key Laboratory of Intelligent Information Processing and Application Hengyang421002 China

Lightweight S-boxes have a significant impact on cryptographic algorithms for resource-constrained devices in the Internet of Things (IoT). Previous research on such S-oxes has focused on low area and good cryptographic properties, which neglects the resistance to side-channel analysis, especially differential power analysis (DPA). The reVisited transparency order (VTO) is one of the best indicators for evaluating S-boxes against DPA attacks so far. Therefore, this paper presents a scheme for designing 6-bit S-boxes. The designed S-boxes are suitable for lightweight block ciphers and have a certain ability to resist DPA attacks. Specifically, we first identify 23 3-bit S-boxes with the optimal cryptographic properties and the smallest hardware area through systematic screening. Then, the paper investigates the constructions of lightweight 6-bit S-boxes based on traditional algorithm structures. Finally, a novel structure named F-LM-F is proposed for designing lightweight 6-bit S-boxes by combining Feistel structure and Lai-Massey structure. It has been proven through comparison that the S-boxes under F-LM-F structure achieve fewer fixed points and lower VTO than the 6-bit S-box of BipBip cipher, with a 17.61% reduction in hardware area and a 13.58% decrease in CPU cycles © 2013 IEEE.

关键词： Side channel attack

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Structure-constrain Source Free Domain Adaptation with Regularized Knowledge Distillation of Source Model 13

Structure-constrain Source Free Domain Adaptation with Regul...

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13th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2024

作者： Yang, Dan Peng, Xin Su, Cheng Tan, Dayu Chen, Chaoyang Zhong, Weimin Ministry of Education East China University of Science and Technology Key Laboratory of Smart Manufacturing in Energy Chemical Process Shanghai200237 China Ministry of Education Anhui University Key Laboratory of Intelligent Computing and Signal Processing Anhui Hefei230601 China School of Information and Electrical Engineering Hunan University of Science and Technology Xiangtan China

ISBN: (纸本)9798350361674

Transfer learning aims to leverage the knowledge of the source domain to help the learning of unlabeled target domain models. However, all conventional transfer learning methods assume that samples from source and target domains are always freely accessible. However, this assumption is rarely plausible in real-world due to data privacy. To combat this challenge, we introduce Structure-constrain Source Free Domain Adaptation with regularized Knowledge Distillation of source model (SSFDA-KD). Our method is based on the observations that a deterministic classification result can be obtained when the target data distribution aligns with the source data distribution, and a well-trained model not only yields a deterministic classification for a sample but also has clear category boundaries, which implies samples that are close together belong to the same category. From those, we first generate the source model with labeled source data, which is regarded as a well-trained model. Then, we identify target prototypes with lower self-entropy and assign the pseudo-labels to other samples according to the neighborhood structure. Finally, we refine the target model by minimizing prediction loss, constraining internal structure via triplet loss, and reducing knowledge distillation loss. Experiments of fault diagnosis based on WWTPs are conducted to validate its effectiveness. © 2024 IEEE.

关键词： Domain Knowledge

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