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arXiv 2017年

作者： Li, Erbo Li, Hua EON Reality Inc IrvineCA92618 United States Key lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China

Symmetry detection and discrimination are of fundamental meaning in science, technology, and engineering. This paper introduces reflection invariants and defines the directional moments(DMs) to detect symmetry for shape analysis and object recognition. And it demonstrates that detection of reflection symmetry can be done in a simple way by solving a trigonometric system derived from the DMs, and discrimination of reflection symmetry can be achieved by application of the reflection invariants in 2D and 3D. Rotation symmetry can also be determined based on that. Also, if none of reflection invariants is equal to zero, then there is no symmetry. And the experiments in 2D and 3D show that all the reflection lines or planes can be deterministically found using DMs up to order six. This result can be used to simplify the efforts of symmetry detection in research areas,such as protein structure, model retrieval, reverse engineering, and machine vision etc. Copyright © 2017, The Authors. All rights reserved.

关键词： Object recognition

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Isomorphism between differential and moment invariants under affine transform

arXiv

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arXiv 2017年

The invariant is one of central topics in science, technology and engineering. The differential invariant is essential in understanding or describing some important phenomena or procedures in mathematics, physics, chemistry, biology or computer science etc. The derivation of differential invariants is usually difficult or complicated. This paper reports a discovery that under the affine transform, differential invariants have similar structures with moment invariants up to a scalar function of transform parameters. If moment invariants are known, relative differential invariants can be obtained by the substitution of moments by derivatives with the same order. Whereas moment invariants can be calculated by multiple integrals, this method provides a simple way to derive differential invariants without the need to resolve any equation system. Since the definition of moments on different manifolds or in different dimension of spaces is well established, differential invariants on or in them will also be well defined. Considering that moments have a strong background in mathematics and physics, this technique offers a new view angle to the inner structure of invariants. Projective differential invariants can also be found in this way with a screening process. Copyright © 2017, The Authors. All rights reserved.

关键词： Affine transforms

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B2B2C Platform of National Featured Agricultural Products Design Based on iOS

B2B2C Platform of National Featured Agricultural Products De...

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2017 2nd International Conference on information Technology and Management Engineering（ITME 2017）

作者： Shen-hong LEI Xin-yi CHEN Xiang-he MENG Tao XU Northwest University for Nationalities National languages Information Technology Research Institute Key Lab of China's National Linguistic Information Technology Northwest University for Nationalities Northwest University for Nationalities National Languages Information Technology Research Institute Northwest University for Nationalities Key Laboratory of National language Intelligent Processing

With developing of e-commerce mode, most e-commerce platform only support Chinese browsing interface however development of minority language browsing interface in e-commerce development is neglected. This paper constructed static multilingual approach based on iOS B2B2C e-commerce platform of the Web client system, established a connection between the database and B2B2C platform by database technology. Completing the national featured agricultural products displaying, searching, inquiry, trading, and other functions on i OS e-commerce platform. Through testing on small server website, the Web client system has certain development value and practical value. With the high-speed development of e-commerce, author believes that the platform design achievement will be used widely in the ethnic minority areas.

关键词： iOS system B2B2C mode National language

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Multi-label inductive matrix completion for joint MGMT and IDH1 status prediction for glioma patients 1

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20th International Conference on Medical Image computing and Computer-Assisted Intervention, MICCAI 2017

作者： Chen, Lei Zhang, Han Thung, Kim-Han Liu, Luyan Lu, Junfeng Wu, Jinsong Wang, Qian Shen, Dinggang Jiangsu Key Laboratory of Big Data Security and Intelligent Processing Nanjing University of Posts and Telecommunications Nanjing China Department of Radiology and BRIC University of North Carolina Chapel Hill United States School of Biomedical Engineering Med-X Research Institute Shanghai Jiao Tong University Shanghai China Department of Neurosurgery Huashan Hospital Fudan University Shanghai China Shanghai Key Lab of Medical Image Computing and Computer Assisted Intervention Shanghai China

ISBN: (数字)9783319661858

ISBN: (纸本)9783319661841

MGMT promoter methylation and IDH1 mutation in high-grade gliomas (HGG) have proven to be the two important molecular indicators associated with better prognosis. Traditionally, the statuses of MGMT and IDH1 are obtained via surgical biopsy, which is laborious, invasive and time-consuming. Accurate presurgical prediction of their statuses based on preoperative imaging data is of great clinical value towards better treatment plan. In this paper, we propose a novel Multi-label Inductive Matrix Completion (MIMC) model, highlighted by the online inductive learning strategy, to jointly predict both MGMT and IDH1 statuses. Our MIMC model not only uses the training subjects with possibly missing MGMT/IDH1 labels, but also leverages the unlabeled testing subjects as a supplement to the limited training dataset. More importantly, we learn inductive labels, instead of directly using transductive labels, as the prediction results for the testing subjects, to alleviate the overfitting issue in small-sample-size studies. Furthermore, we design an optimization algorithm with guaranteed convergence based on the block coordinate descent method to solve the multivariate non-smooth MIMC model. Finally, by using a precious single-center multi-modality presurgical brain imaging and genetic dataset of primary HGG, we demonstrate that our method can produce accurate prediction results, outperforming the previous widely-used single- or multi-task machine learning methods. This study shows the promise of utilizing imaging-derived brain connectome phenotypes for prognosis of HGG in a non-invasive manner. © Springer International Publishing AG 2017.

关键词： Forecasting

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A Novel Soft Switching Two-Stage Heating Power Supply Topology for Silicon Growth Furnace 35

A Novel Soft Switching Two-Stage Heating Power Supply Topolo...

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第35届中国控制会议

作者： GUO Xin REN Hai-Peng LIU Ding SUO Jun PENG Shu-Tao School of Automation and Information Engineering Xi'an University of Technology Shaanxi Key Lab.of Complex System Control and Intelligent Information Processing Shaanxi Electric Power Research Institute

ISBN: (纸本)9781509009107

Mono-crystalline silicon is widely applied in the photovoltaic and the integrated circuit *** power supply,as the key element of the mono-crystalline silicon growth furnace,plays an important role in the performance of the whole *** this paper,we propose a new kind of two-stage silicon growth furnace heating power supply topology *** first stage three phase rectifier employs the compound active clamp zero voltage soft switching(CACZVS) three-phase power factor correction(PFC) converter to achieve unity power factor and DC bus voltage regulation,and the second stage DC/DC converter employs phase shifted full bridge zero voltage and zero current soft switching converter(FB-ZVZCS) to regulate the output *** with the heating power supply of non-controlled rectifier type or three-phase power factor correction circuit using hard switching,the proposed two-stage converter structure can achieve high power factor,high efficiency and more flexibility of *** simulation results show the correctness of the analysis.

关键词： Silicon Growth Furnace Heating Power Supply CACZVS three phase PFC converter FB-ZVZCS converter

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Abstractive news summarization based on event semantic link network 26

Abstractive news summarization based on event semantic link ...

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26th International Conference on Computational Linguistics, COLING 2016

作者： Li, Wei He, Lei Zhuge, Hai Key Lab. of Intelligent Information Processing Institute of Computing Technology University of Chinese Academy of Sciences Beijing China Aston University Birmingham United Kingdom

ISBN: (纸本)9784879747020

This paper studies the abstractive multi-document summarization for event-oriented news texts through event information extraction and abstract representation. Fine-grained event mentions and semantic relations between them are extracted to build a unified and connected event semantic link network, an abstract representation of source texts. A network reduction algorithm is proposed to summarize the most salient and coherent event information. New sentences with good linguistic quality are automatically generated and selected through sentences over-generation and greedy-selection processes. Experimental results on DUC 2006 and DUC 2007 datasets show that our system significantly outperforms the state-of-the-art extractive and abstractive baselines under both pyramid and ROUGE evaluation metrics. © 1963-2018 ACL.

关键词： Semantics

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Memory-enhanced Decoder for neural machine translation

Memory-enhanced Decoder for neural machine translation

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2016 Conference on Empirical Methods in Natural Language processing, EMNLP 2016

作者： Wang, Mingxuan Lu, Zhengdong Li, Hang Liu, Qun Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China Noah's Ark Lab Huawei Technologies ADAPT Centre School of Computing Dublin City University Ireland

ISBN: (纸本)9781945626258

We propose to enhance the RNN decoder in a neural machine translator (NMT) with external memory, as a natural but powerful extension to the state in the decoding RNN. This memory-enhanced RNN decoder is called MEMDEC. At each time during decoding, MEMDEC will read from this memory and write to this memory once, both with content-based addressing. Unlike the unbounded memory in previous work(Bahdanau et al., 2014) to store the representation of source sentence, the memory in MEMDEC is a matrix with predetermined size designed to better capture the information important for the decoding process at each time step. Our empirical study on Chinese-English translation shows that it can improve by 4.8 BLEU upon Groundhog and 5.3 BLEU upon on Moses, yielding the best performance achieved with the same training set. © 2016 Association for Computational Linguistics

关键词： Neural machine translation

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多组学基因大数据与精准医学

多组学基因大数据与精准医学

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浙江省生物信息学学会第五届学术年会暨大数据时代精准医学国际学术研讨会

作者： Yi Zhao Bioinformatics Research Group Key Laboratory of Intelligent Information ProcessingAdvanced Computing Research LaboratoryInstitute of Computing TechnologyChineseAcademy of Sciences LuoYang Branch of Institute of Computing Technology Chinese Academy of Sciences

伴随着高通量测序技术等生物技术的发展,基因组、转录组、表观组、蛋白组、代谢组、微生物组、暴露组等多组学测序数据可以在几天之内迅速产出,并被广泛应用于精准医学的研究和临床应用,这些庞大而复杂的数据不但构成了精确医学所需要... 详细信息

伴随着高通量测序技术等生物技术的发展,基因组、转录组、表观组、蛋白组、代谢组、微生物组、暴露组等多组学测序数据可以在几天之内迅速产出,并被广泛应用于精准医学的研究和临床应用,这些庞大而复杂的数据不但构成了精确医学所需要的关键信息,而且也是该领域内增长最快的数据类型。当前,精准医学计划在多个国家陆续启动,各国科学家们正致力于收集十万、百万人群的基因组信息用来构建权威、且全新的人口健康大数据知识体系。在这样的时代背景下,作为人口大国,中国精准医学迫切的需要建立属于中国人自己的基因数据库。2016年,中国科技部将"精准医学研究"列为重大研究计划,中科院也于2016年启动中国人群精准医学研究计划,4年内预计完成4000志愿者的DNA样本和多种表现型数据的采集。对此,我们可以预见,随着大队列研究的开展,以基因组为代表的多组学大数据仍将会不断产生,但是这些组学大数据本身并不能产生价值,其价值在于与疾病表型等其他信息进行关联分析、挖掘并转换为知识,才能进一步被应用于医疗及健康决策。因此,促进大数据到知识的转化,构建基因大数据研究与应用的一体化平台体系,才是精准医学到临床的关键一步,其将会被应用于疾病的早期筛查、分子分型、个体化治疗、疗效预测及监控等多个临床决策场景。多组学精准医学大数据的发展和研究也面临着一些挑战,例如:数据共享与安全隐私问题、多维度组学数据的整合分析问题、生物信息数据分析方法的标准化以及解读规范化等等问题。因此,需要更多国家政策的支持、需要IT及人工智能等领域的学者贡献力量、需要各个领域的专家来制定行业标准,最终推动精准医疗向自动化,智能化,标准化,简单化方向发展。

关键词：精准医学多组学大数据

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COMRANCE: A rapid method for Network-on-Chip design space exploration 7

COMRANCE: A rapid method for Network-on-Chip design space ex...

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7th International Green and Sustainable computing Conference, IGSC 2016

作者： Zhang, Mingzhe Shi, Yangguang Zhang, Fa Liu, Zhiyong Beijing Key Laboratory of Mobile Computing and Pervasive Device ICT CAS Beijing China University of Chinese Academy of Sciences Beijing China Key Lab of Intelligent Information Processing ICT CAS Beijing China

ISBN: (纸本)9781509051175

As the communication sub-system that connecting various on-chip components, Network-on-Chip (NoC) has a great influence on the performance of multi-/many-core processors. Because of NoC model contains a large number of parameters, the design space exploration (DSE) for NoC is a critical problem for the architects. Similar to the core design, existing DSE process mainly depends on iteratively time-consuming simulations. To lower the time budget, many previous studies focus on reducing the simulations. However, most of the proposed works based on regression or machine learning techniques, whose accuracy will be significantly affected by the scale of training set. It still needs a lot of simulations to build the training set. © 2016 IEEE.

关键词： Network-on-chip

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Cloud service resource allocation with particle swarm optimization algorithm 12th

Cloud service resource allocation with particle swarm optimi...

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12th International Conference on Bio-Inspired computing: Theories and Applications, BIC-TA 2017

作者： Cheng, Shi Guo, Lantian Yang, Tao Feng, Jiqiang Sun, Yifei Shao, Chang Duan, Qiqi School of Computer Science Shaanxi Normal University Xi’an China Shenzhen Research Institute Northwestern Polytechnical University Shenzhen China School of Automation Northwestern Polytechnical University Xi’an China Institute of Intelligent Computing Science Shenzhen University Shenzhen China School of Physics and Information Technology Shaanxi Normal University Xi’an China Shenzhen Key Lab of Computational Intelligence Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China

ISBN: (纸本)9789811071782

Cloud service resource allocation is an essential task in cloud computing. The cloud service resource allocation problem is modeled as an optimization problem, and is solved via different particle swarm optimization (PSO) variants in this paper. The aim of our method is to minimize the delay and the price at the same time. Based on the experimental results, it could be conducted that the good performance could be achieved via PSO algorithms. The future research is to utilize PSO algorithms on solving more real-world problems, especially with other quality of service problems. © Springer Nature Singapore Pte Ltd 2017.

关键词： Swarm intelligence

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