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International Conference on Pattern Recognition

作者： Vijeta Khare Palaiahnakote Shivakumara B.J. Navya G.C. Swetha D. S. Guru Umapada Pal Tong Lu Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur Malaysia Department of Studies in Computer Science University of Mysore Karnataka India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India National Key Lab for Novel Software Technology Nanjing University Nanjing China

Text line segmentation from handwritten documents is challenging when a document image contains severe touching. In this paper, we propose a new idea based on Weighted-Gradient Features (WGF) for segmenting text lines. The proposed method finds the number of zero crossing points for every row of Canny edge image of the input one, which is considered as the weights of respective rows. The weights are then multiplied with gradient values of respective rows of the image to widen the gap between pixels in the middle portion of text and the other portions. Next, k-means clustering is performed on WGF to classify middle and other pixels of text. The method performs morphological operation to obtain word components as patches for the result of clustering. The patches in both the clusters are matched to find common patch areas, which helps in reducing touching effect. Then the proposed method checks linearity and non-linearity iteratively based on patch direction to segment text lines. The method is tested on our own and standard datasets, namely, Alaei, ICDAR 2013 robust competition on handwriting context and ICDAR 2015-HTR, to evaluate the performance. Further, the method is compared with the state of art methods to show its effectiveness and usefulness.

关键词： Image segmentation Image edge detection Linearity Writing Morphological operations Handwriting recognition Image restoration

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Ultrastrong magnon-magnon coupling dominated by antiresonant interactions

arXiv

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arXiv 2020年

作者： Makihara, Takuma Hayashida, Kenji Noe, G. Timothy Li, Xinwei Peraca, Nicolas Marquez Ma, Xiaoxuan Jin, Zuanming Ren, Wei Ma, Guohong Katayama, Ikufumi Takeda, Jun Nojiri, Hiroyuki Turchinovich, Dmitry Cao, Shixun Bamba, Motoaki Kono, Junichiro Department of Physics and Astronomy Rice University HoustonTX United States Department of Electrical and Computer Engineering Rice University HoustonTX United States Division of Applied Physics Graduate School Faculty of Engineering Hokkaido University Sapporo Hokkaido060-8628 Japan Department of Physics International Center of Quantum and Molecular Structures and Materials Genome Institute Shanghai University Shanghai200444 China Terahertz Technology Innovation Research Institute Terahertz Spectrum and Imaging Technology Cooperative Innovation Center Shanghai Key Lab of Modern Optical System University of Shanghai for Science and Technology 516 JunGong Road Shanghai200093 China Department of Physics Graduate School of Engineering Science Yokohama National University Yokohama Japan Institute for Materials Research Tohoku University Sendai Japan Fakultät für Physik Universität Bielefeld Universitätsstr. 25 Bielefeld33615 Germany Department of Physics Kyoto University Sakyo-ku Kyoto606-8502 Japan PRESTO Japan Science and Technology Agency Saitama332-0012 Japan Department of Materials Science and NanoEngineering Rice University HoustonTX United States

Exotic quantum vacuum phenomena are predicted in cavity quantum electrodynamics (QED) systems with ultrastrong light-matter interactions. Their ground states are predicted to be vacuum squeezed states with suppressed quantum fluctuations. The source of such phenomena is antiresonant terms in the Hamiltonian, yet antiresonant interactions are typically negligible compared to resonant interactions in light-matter systems. We report an unusual, ultrastrongly coupled matter-matter system of magnons that is analytically described by a unique Hamiltonian in which the relative importance of resonant and antiresonant interactions can be easily tuned and the latter can be made vastly dominant. We found a novel regime where vacuum Bloch-Siegert shifts, the hallmark of antiresonant interactions, greatly exceed analogous frequency shifts from resonant interactions. Further, we theoretically explored the system's ground state and calculated up to 5.9 dB of quantum fluctuation suppression. These observations demonstrate that magnonic systems provide an ideal platform for exploring exotic quantum vacuum phenomena predicted in ultrastrongly coupled light-matter systems. Copyright © 2020, The Authors. All rights reserved.

关键词： Hamiltonians

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Efficient identity-based threshold decryption scheme from bilinear pairings

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Frontiers of computer science 2018年第1期12卷 177-189页

作者： Wei GAO Guilin WANG Kefei CHEN Xueli WANG School of Mathematics and Statistics Ludong University Yantai 264025 China School of Computer and Software Nanjing University of Information Science & Technology Nanjing 210044 China Key Laboratory of Information Security Guangzhou University Guangzhou 510006 China Shield Lab Singapore Research Center of Huawei Singapore 117674 Singapore Department of Mathematics Hangzhou Normal University Hangzhou 311121China School of Mathematics South China Normal University Guangzhou 510631 China

Using Shamir＇s secret sharing scheme to indi- rectly share the identity-based private key in the form of a pairing group element, we propose an efficient identity-based threshold decryption scheme from pairings and prove its se- curity in the random oracle model. This new paring-based scheme features a few improvements compared with other schemes in the literature. The two most noticeable features are its efficiency, by drastically reducing the number of pair- ing computations, and the ability it gives the user to share the identity-based private key without requiring any access to a private key generator. With the ability it gives the user to share the identity-based private key, our ID-based threshold decryption （IBTD） scheme, the second of its kind, is signif- icantly more efficient than the first scheme, which was de- veloped by Baek and Zheng, at the expense of a slightly in- creased ciphertext length. In fact, our IBTD scheme tries to use as few bilinear pairings as possible, especially without depending on the suite of Baek-Zheng secret sharing tools based on pairings.

关键词： identity-based cryptography threshold cryptog-raphy provable security random oracle model bilinear pair-ing identity-based threshold decryption

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Quantum supremacy circuit simulation on sunway taihulight

arXiv

引用

arXiv 2018年

作者： Li, Riling Wu, Bujiao Ying, Mingsheng Sun, Xiaoming Yang, Guangwen Department of Computer Science & Technology Tsinghua University Beijing China CAS Key Lab of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences Beijing China Centre for Quantum Software and Information University of Technology Sydney Sydney Australia State Key Lab of Computer Science Institute of Software Chinese Academy of Sciences Department of Computer Science & Technology Tsinghua University Beijing China

With the rapid progress made by industry and academia, quantum computers with dozens of qubits or even larger size are being realized. However, the fidelity of existing quantum computers often sharply decreases as the circuit depth increases. Thus, an ideal quantum circuit simulator on classical computers, especially on high-performance computers, is needed for benchmarking and validation. We design a large-scale simulator of universal random quantum circuits, often called "quantum supremacy circuits", and implement it on Sunway TaihuLight. The simulator can be used to accomplish the following two tasks: 1) Computing a complete output state-vector;2) Calculating one or a few amplitudes. We target the simulation of 49-qubit circuits. For task 1), we successfully simulate such a circuit of depth 39, and for task 2) we reach the 55-depth level. To the best of our knowledge, both of the simulation results reach the largest depth for 49-qubit quantum supremacy circuits. Copyright © 2018, The Authors. All rights reserved.

关键词： Circuit simulation

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Graph-Based Methods for Ontology Summarization: A Survey

Graph-Based Methods for Ontology Summarization: A Survey

引用

Artificial Intelligence and Knowledge Engineering (AIKE)

作者： Seyedamin Pouriyeh Mehdi Allahyari Qingxia Liu Gong Cheng Hamid Reza Arabnia Maurizio Atzori Krys Kochut Computer Science Department University of Georgia Athens GA USA Computer Science Department Georgia Southern University Statesboro USA National Key Laboratory for Novel Software Technology Nanjing University Nanjing China Math/CS Department University of Cagliari Italy

ISBN: (纸本)9781538695562;9781538660843

Ontologies have been widely used in numerous and varied applications, e.g., to support data modeling, information integration, and knowledge management. With the increasing size of ontologies, ontology understanding, which is playing an important role in different tasks, is becoming more difficult. Consequently, ontology summarization, as a way to distill key information from an ontology and generate an abridged version to facilitate a better understanding, is getting growing attention. In this survey paper, we review existing ontology summarization techniques and focus mainly on graph-based methods, which represent an ontology as a graph and apply centrality-based and other measures to identify the most important elements of an ontology as its summary. After analyzing their strengths and weaknesses, we highlight a few potential directions for future research.

关键词： Resource description framework Ontologies Vocabulary OWL Task analysis Knowledge based systems

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Multi-Gradient Directional Features for Gender Identification

Multi-Gradient Directional Features for Gender Identificatio...

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International Conference on Pattern Recognition

作者： B.J. Navya G. C. Swetha Palaiahnakote Shivakumara Sangheeta Roy D. S. Guru Umapada Pal Tong Lu Department of Studies in Computer Science University of Mysore Karnataka India Faculty of Computer System and Information Technology University of Malaya Kuala Lumpur Malaysia Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India National Key Lab for Novel Software Technology Nanjing University Nanjing China

Gender identification based on handwriting analysis has received a special attention to researchers in the field of document image analysis as it is useful for several real-time applications like forensic, population counting, etc. In this paper, we explore Multi-Gradient Directional (MGD) features, which provide direction of dominant pixels obtained by Canny edge image, and gradient direction symmetry. The proposed method further performs histogram operation for gradient angle information of dominant pixels of respective multi-gradient directional images to select angles, which contribute to the highest peak. This results in feature vectors. The process of feature vector formation continues for the segmented first, second, and third text lines in each image by male or female. Next, correlation is estimated for the vector of the first line with successive lines until converging or diverging criteria is met. If the convergence happens, a document is considered as by female, else is considered as by male. The method is tested on our own dataset, which includes images of different scripts, writers, papers, pens, and ages, and the standard database QUWI which includes Arabic and English texts, to demonstrate the efficiency of the proposed method. Comparative studies with the state of the art methods show that the proposed method is effective and useful.

关键词： Feature extraction Image edge detection Writing Junctions Histograms Face Support vector machines

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Adaptive Multi-Gradient Kernels for Handwritting Based Gender Identification

Adaptive Multi-Gradient Kernels for Handwritting Based Gende...

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International Workshop on Frontiers in Handwriting Recognition

作者： B. J Navya Palaiahnakote Shivakumara G.C Shwetha Sangheeta Roy D. S. Guru Umapada Pal Tong Lu Department of Studies in Computer Science University of Mysore Karnataka India Faculty of Computer System and Information Technology University of Malaya Kuala Lumpur Malaysia Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India National Key Lab for Novel Software Technology Nanjing University Nanjing China

Handwriting based Gender identification is challenging due to unconstrained handwriting and individual differences in writing. To solve this problem, we propose a new adaptive multi-gradient of Sobel kernels for extracting Adaptive Multi-Gradient Features (AMGF). For extracted text lines, the proposed method finds dominant pixels based on directional symmetry of text pixels given by AMGF. We perform histogram operation for adaptive multi-gradient values extracted corresponding to dominant pixels. The gradient values that give the highest peak in respective histograms is chosen as features. This results in feature vector having four AMGF values. The same vector are generated for successive text lines in each image to study either consistency, which is expected for females or inconsistency, which is expected for males in writing styles. The correlation is estimated based on feature vectors of the first and the successive text lines until converging or diverging criteria is met. If convergence happens, the input document is considered as female else is considered as male. The method is tested on our own dataset, which includes large variations and standard datasets, namely, QUWI, IAM-1+IAM-2 and KHATT, to demonstrate the effectiveness of the proposed method. Experimental results show that the proposed method outperforms the existing methods.

关键词： Feature extraction Kernel Image edge detection Writing Histograms Junctions Laplace equations

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Agent with Warm Start and Active Termination for Plane Localization in 3D Ultrasound

arXiv

引用

arXiv 2019年

作者： Dou, Haoran Yang, Xin Qian, Jikuan Xue, Wufeng Qin, Hao Wang, Xu Yu, Lequan Wang, Shujun Xiong, Yi Heng, Pheng-Ann Ni, Dong National-Regional Key Technology Engineering Laboratory for Medical Ultrasound Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging School of Biomedical Engineering Health Science Center Shenzhen University Shenzhen China Lab China Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong Department of Ultrasound Luohu People's Hospital Shenzhen China

Standard plane localization is crucial for ultrasound (US) diagnosis. In prenatal US, dozens of standard planes are manually acquired with a 2D probe. It is time-consuming and operator-dependent. In comparison, 3D US containing multiple standard planes in one shot has the inherent advantages of less user-dependency and more efficiency. However, manual plane localization in US volume is challenging due to the huge search space and large fetal posture variation. In this study, we propose a novel reinforcement learning (RL) framework to automatically localize fetal brain standard planes in 3D US. Our contribution is twofold. First, we equip the RL framework with a landmark-aware alignment module to provide warm start and strong spatial bounds for the agent actions, thus ensuring its effectiveness. Second, instead of passively and empirically terminating the agent inference, we propose a recurrent neural network based strategy for active termination of the agent's interaction procedure. This improves both the accuracy and efficiency of the localization system. Extensively validated on our in-house large dataset, our approach achieves the accuracy of 3.4mm/9.6◦ and 2.7mm/9.1◦ for the transcerebellar and transthalamic plane localization, respectively. Our proposed RL framework is general and has the potential to improve the efficiency and standardization of US scanning. © 2019, CC BY.

关键词： Reinforcement learning

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Application-centric SSD cache allocation for hadoop applications 17

Application-centric SSD cache allocation for hadoop applicat...

引用

9th Asia-Pacific Symposium on Internetware, Internetware 2017

作者： Tang, Zhen Wang, Wei Huang, Yu Wu, Heng Wei, Jun Huang, Tao State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences University of Chinese Academy of Sciences China State Key Laboratory for Novel Software Technology Department of Computer Science and Technology Nanjing University China

ISBN: (纸本)1595930361

Flash-based Solid State Drive (SSD) is widely used in the virtualization environment, usually as the cache of the hard disk drive-based Virtual Machine (VM) storage, to improve the IO performance. Existing SSD caching schemes are mainly driven by VM-centric metrics. They treat the VMs as independent units and focus on critical low-level performance metrics of individual VMs, such as the working set, the IO latency, or the throughput. However, for elastic Hadoop applications consisting of multiple VMs, the workload is rapidly changing, and the importance of differnet VMs may be different even if they have the same low-level IO pattern. In this situation, the VM-centric SSD caching schemes may not lead to the best performance, i.e., the shortest job completion time. Considering the importance of VMs and relationships among VMs inside the application may potentially better improve the performance, which we regard as the application-centric metrics. We propose the Application-Centric SSD caching for Hadoop applications (ACSSD), which reduces the job completion time from the application level. AC-SSD uses the genetic algorithm based approach to calculate the nearly optimal weights of virtual machines for allocating SSD cache space and controlling the I/O Operations Per Second (IOPS) based on the importance of the VMs. Moreover, AC-SSD introduces the closed-loop adaptation to face the rapidly changing workload. The evaluation shows that AC-SSD reduces the job completion time by up to 39% for IO sensitive workloads, and up to 29% for rapidly changing workloads. © 2017 Association for Computing Machinery.

关键词： Virtualization

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A New RGB Based Fusion for Forged IMEI Number Detection in Mobile Images

A New RGB Based Fusion for Forged IMEI Number Detection in M...

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International Workshop on Frontiers in Handwriting Recognition

作者： Palaiahnakote Shivakumara V. Basavaraja Harsha S. Gowda D. S. Guru Umapada Pal Tong Lu Faculty of Computer System and Information Technology University of Malaya Kuala Lumpur Malaysia Department of Studies in Computer Science University of Mysore Mysore Karnataka India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India National Key Lab for Novel Software Technology Nanjing University Nanjing China

As technology advances to make living comfortable for people, at the same time, different crimes also increase. One such sensitive crime is creating fake International Mobile Equipment Identity (IMEI) for smart mobile devices. In this paper, we present a new fusion based method using R, G and B color components for detecting forged IMEI numbers. To the best of our knowledge, this is the first work for forged IMEI number detection in mobile images. The proposed method first finds variances for R, G and B images of a forged input image to study local changes. The variances are used to derive weights for respective color components. The same weights are convolved with respective pixel values of R, G and B components, which results in the fused image. For the fused image, the proposed method extracts features based on sparsity, the number of connected components, and the average intensity values for edge components in respective R, G and B components, which gives six features. The proposed method finds absolute difference between fused and input images, which gives feature vector containing six difference values. The proposed method constructs templates based on samples chosen randomly. Feature vectors are compared with the templates for detecting forged IMEI numbers. Experiments are conducted on our own dataset and standard datasets to evaluate the proposed method. Furthermore, comparative studies with the related existing methods show that the proposed method outperforms the existing methods.

关键词： Feature extraction Image color analysis Image edge detection Forgery software Printers Image segmentation

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