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Sixth International Conference on Semantics,Knowledge and Grids(第六届语义、知识与网格国际会议 SKG 2010)

作者： Xiaorui Jiang Xiaoping Sun Hai Zhuge Knowledge Grid Research Group Key Lab of Intelligent Information Processing Institute of Computing Technology CAS Beijing China

Dataspace is a semi-structural data model for the management of large-scale heterogeneous data *** a dataspace,each data object consists of a set of attribute-value pairs to describe the internal properties of the object and their relationships to other objects. The dataspace model provides a flexible query language that supports attribute-value pair-based predicate queries and semantic link queries. In this paper we introduce a Resource Space Model that extends the concepts of dataspace to make it more flexible by incorporating classification semantics. We model a dataspace as a set of Resource Spaces (RS) with each RS representing a kind of resources that share common attributes and can be put into the same category, either according to a user’s knowledge of the world or his query preferences. Our model is suitable for designing a user-tailored semantic view of a dataspace while at the same time without losing the schema-later data-centric nature. A practical query language is introduced to implement flexible query operations on the resource spaces of the dataspace. Examples show how the proposed model and language support both the schema query and the data query.

关键词： Semantics Data models Argon Portals Organizations Database languages Resource description framework

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Summarization of Related Work through Citations 12

Summarization of Related Work through Citations

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12th International Conference on Semantics, Knowledge and Grids, SKG 2016

作者： Chen, Jingqiang Zhuge, Hai Nanjing University of Posts and Telecommunications 210023 Nanjing China. Key Lab of Intelligent Information Processing Institute of Computing Technology University of Chinese Academy of Sciences 100190 Beijing China. Systems Analytics Research Institute Aston University Birmingham UK

ISBN: (纸本)9781509047956

Automatically generating the related work section for a writing paper is useful for researchers as it can save a lot of time and avoid missing related works. The related work section of scientific paper usually introduces other researchers' work published before and makes comparisons with the current author's work. This paper proposes an approach to automatically generating related work by comparing the main text of the writing paper with the citations to the references from other papers. Our approach firstly collects the papers that cite the reference papers of the writing paper and extracts the corresponding citation sentences to form a citation document. It then makes a summarization that makes a comparison between the citation document and the writing paper's abstract, introduction and conclusion. It extracts the representative keywords from the citation document and the writing paper, and constructs a graph of the keywords. The discriminated nodes in the graph are figured out, and then the minimum Steiner tree that covers the nodes is extracted. A summary is generated by extracting the sentences covering the Steiner tree. The experiments show that our approach outperforms three baselines MEAD, ReWoS and ARWG according to ROUGE evaluation results. © 2016 IEEE.

关键词： Trees (mathematics)

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Preface-GCIS 2013

Proceedings - 2013 4th Global Congress on Intelligent System...

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Proceedings - 2013 4th Global Congress on intelligent Systems, GCIS 2013 2013年 xi-xii页

作者： Xu, Li Da Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China

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Dual-photoconductivity in monolayer PtSe_(2) ribbons

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Nano research 2024年第11期17卷 10189-10195页

作者： Zechen Li Honglin Wang Huaipeng Wang Jing Li Fangzhu Qing Xuesong Li Dan Xie Hongwei Zhu State Key Lab of New Ceramics and Fine Processing School of Materials Science and Engineering Tsinghua University Beijing 100084 China School of Integrated Circuits Beijing National Research Center for Information Science and Technology Tsinghua University Beijing 100084 China State Key Lab of Solid Waste Reuse for Building Materials Beijing Building Materials Academy of Science Research Beijing 100041 China Shenzhen Institute for Advanced Study University of Electronic Science and Technology of China Shenzhen 518110 China

Two-dimensional platinum diselenide (PtSe_(2)) has been explored for applications in visible and infrared photodetectors, owing to its tunable electrical and optoelectronic properties governed by layer-dependent bandgaps. Studies have explored both positive photoconductivity (PPC) and negative photoconductivity (NPC) behaviors in few-layer PtSe_(2) thin films, proposing mechanisms related to gas molecule adsorption. However, these proposed mechanisms, typically based on models with ideal limit structures, often lacked consistency with the structure and scale of polycrystalline thin films employed in actual experiments. Here, photodetectors utilizing monolayer PtSe_(2) ribbons were designed, demonstrating a significant NPC effect upon exposure to visible light in atmospheric conditions, with device resistance increasing to over threefold the initial state. Under vacuum conditions, the device demonstrated PPC characteristics. Density functional theory calculations indicated that oxygen molecules physically adsorbed at the edges of PtSe_(2) ribbons were integral. Laser irradiation prompted the detachment of oxygen molecules from the ribbon’s edges, leading to a decreased carrier concentration in channel conductivity. The abundant edge sites of the ribbons endowed the photodetectors with a pronounced NPC response. This study diverted from traditional multilayer PtSe_(2) films to explore monolayer PtSe_(2) ribbons. These ribbons, as limit structures, offered a more fundamental insight into the intrinsic photoconductivity properties of PtSe_(2). Photodetectors employing PtSe_(2) ribbons presented novel application prospects in low-power photodetection, gas detection, and additional fields.

关键词： platinum diselenide photodetector negative photoconductivity positive photoconductivity photoinduced desorption

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Bilingually-constrained (monolingual) shift-reduce parsing

Bilingually-constrained (monolingual) shift-reduce parsing

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2009 Conference on Empirical Methods in Natural Language processing, EMNLP 2009, Held in Conjunction with ACL-IJCNLP 2009

作者： Huang, Liang Jiang, Wenbin Liu, Qun Google Research 1350 Charleston Rd. Mountain View CA 94043 United States Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences P.O. Box 2704 Beijing 100190 China

Jointly parsing two languages has been shown to improve accuracies on either or both sides. However, its search space is much bigger than the monolingual case, forcing existing approaches to employ complicated modeling and crude approximations. Here we propose a much simpler alternative, bilingually-constrained monolingual parsing, where a source-language parser learns to exploit reorderings as additional observation, but not bothering to build the target-side tree as well. We show specifically how to enhance a shift-reduce dependency parser with alignment features to resolve shift-reduce conflicts. Experiments on the bilingual portion of Chinese Treebank show that, with just 3 bilingual features, we can improve parsing accuracies by 0.6% (absolute) for both English and Chinese over a state-of-the-art baseline, with negligible (∼6%) efficiency overhead, thus much faster than biparsing. © 2009 ACL and AFNLP.

关键词： Forestry

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Occlusion-free Face Alignment: Deep Regression Networks Coupled with De-corrupt AutoEncoders

Occlusion-free Face Alignment: Deep Regression Networks Coup...

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IEEE Conference on Computer Vision and Pattern Recognition

作者： Jie Zhang Meina Kan Shiguang Shan Xilin Chen Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS) Institute of Computing Technology

ISBN: (纸本)9781467388528

Face alignment or facial landmark detection plays an important role in many computer vision applications, e.g., face recognition, facial expression recognition, face animation, etc. However, the performance of face alignment system degenerates severely when occlusions occur. In this work, we propose a novel face alignment method, which cascades several Deep Regression networks coupled with De-corrupt Autoencoders (denoted as DRDA) to explicitly handle partial occlusion problem. Different from the previous works that can only detect occlusions and discard the occluded parts, our proposed de-corrupt autoencoder network can automatically recover the genuine appearance for the occluded parts and the recovered parts can be leveraged together with those non-occluded parts for more accurate alignment. By coupling de-corrupt autoencoders with deep regression networks, a deep alignment model robust to partial occlusions is achieved. Besides, our method can localize occluded regions rather than merely predict whether the landmarks are occluded. Experiments on two challenging occluded face datasets demonstrate that our method significantly outperforms the state-of-the-art methods.

关键词： Occlusion Face Face occluding landmarks Alignment Regression (Psychology) Facial Recognition images computer vision coupling

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Radar Echo Modeling and Doppler Characteristic Fitting Method for UAVs Based on Multi-Scattering Point Model 2

Radar Echo Modeling and Doppler Characteristic Fitting Metho...

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2nd IEEE International Conference on Signal, information and Data processing, ICSIDP 2024

作者： Xu, Li'Ang Jiang, Qi Wang, Rui Zhang, Jichuan Jiao, Longxiang Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing China Beijing Institute of Technology Advanced Technology Research Institute Beijing China

ISBN: (纸本)9798331515669

The radar echo characteristics of unmanned aerial vehicles provide important information for identification. The radar echoes of various types of UAVs are modeled by the multi-scattering point modeling method. A Doppler characteristic modeling method for unmanned aerial vehicles based on the mixture Gaussian algorithm is proposed, in which the slow-time dimension data are extracted from the Range- Doppler and fitted by the mixture Gaussian algorithm. The parameters of the Gaussian distribution components representing the unmanned aerial vehicle's Doppler spread characteristics are obtained using the algorithm. The simulated radar echoes of the multi-rotor unmanned aerial vehicle and the flapping-wing unmanned aerial vehicle are used for analysis. The performance of the fitting is acceptable and the way in which various parameters affect the Doppler characteristics is discussed and concluded. © 2024 IEEE.

关键词： Gaussian distribution

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Collecting valuable information from fast text streams 8

Collecting valuable information from fast text streams

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8th IFIP International Conference on intelligent information processing, IIP 2014

作者： Qi, Baoyuan Ma, Gang Shi, Zhongzhi Wang, Wei Key Lab of Intelligent Information Processing Institute of Computing Technology CAS Beijing100190 China University of Chinese Academy of Sciences Beijing100190 China Beijing Lexo Technologies Co. Ltd Beijing100080 China

ISBN: (纸本)9783662449790

It has become a challenging work to collect valuable information from fast text streams. In this work, we propose a method which gains useful information effectively and efficiently. Firstly, we maintain an analyzer based on the Trie structure and the dynamic N-Gram tokenizer;secondly, unlike the traditional search engine principle, we consider the documents as a query by building the indexes for the whole query base. The experimental results show that it has the strong adaption ability, low latency and high quality support for the complex query combination compared with the conventional methods. © IFIP International Federation for information processing 2014.

关键词： Search engines

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A method for enhancing infrared small target images under complex sky backgrounds 2

A method for enhancing infrared small target images under co...

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2nd IEEE International Conference on Signal, information and Data processing, ICSIDP 2024

作者： Xu, Yuhan Tang, Linbo Sun, Haotian Beijing Institute of Technology Beijing Key Laboratory of Embedded Real-Time Information Processing Radar Research Lab School of Information and Electronics Beijing China Advanced Technology Research Institute Beijing Institute of Technology Jinan250300 China

ISBN: (纸本)9798331515669

Infrared target detection is currently widely used in both military and civilian fields. Due to the lower resolution of infrared images compared to visible light images and the lack of texture information in small targets, the quality of infrared small target images is often poor and not suitable for direct detection. Therefore, enhancing low-quality infrared small target images is a necessary step before object detection can be performed. This article presents a method for enhancing infrared images of small targets. The process begins with applying guided filtering to the original image. The resulting detail layer is then used as a guided image for a second guided filtering of the base layer, producing a second detail layer. Additionally, a novel approach to local contrast enhancement is introduced, which applies contrast enhancement specifically to this secondary detail layer. Experimental results has been demonstrated that the enhancement method proposed in this paper significantly improves the visibility of the target area while reducing background interference, without losing information about small targets. Additionally, this method outperforms other common techniques in terms of enhancement effect, as shown in comparative experiments. © 2024 IEEE.

关键词： Wiener filtering

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Frequency recovery of band-limited seismic data based on sparse spike train deconvolution 77

Frequency recovery of band-limited seismic data based on spa...

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77th Society of Exploration Geophysicists International Exposition and Annual Meeting, SEG 2007

作者： Lu, Wen-Kai Liu, Dong-Qi Key State Lab. of Intelligent Technology and System Institute of Information Processing Department of Automation Tsinghua University China Institute of Geophysics PetroChina Research Institute of Petroleum Exploration and Development China

ISBN: (纸本)9781604238976

An iterative algorithm is presented for the frequency recovery of the band-limited seismic data based on the sparse spike train deconvolution (SSTD) method using the minimum entropy criterion. In this method, we exploit an upper limit nonlinear function to construct a new entropy measure, which is insensitive to the large value. Furthermore, a parameter of the nonlinear function is adopted to control the sparsity of the deconvolved signal. Synthetic data experiments are provided and the results show that this method performs well at low computation time. © 2007 Society of Exploration Geophysicists. All rights reserved.

关键词： Functions

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