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arXiv 2017年

作者： Lang, Guangming School of Mathematics and Statistics Changsha University of Science and Technology Changsha Hunan410114 China Department of Computer Science and Technology Tongji University Shanghai201804 China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai201804 China College of Mathematics and Econometrics Hunan University Changsha Hunan410004 China

In practical situations, there are many dynamic covering information systems with variations of attributes, but there are few studies on related family-based attribute reduction of dynamic covering information systems. In this paper, we first investigate updated mechanisms of constructing attribute reducts for consistent and inconsistent covering information systems when varying attribute sets by using related families. Then we employ examples to illustrate how to compute attribute reducts of dynamic covering information systems with variations of attribute sets. Finally, the experimental results illustrates that the related family-based methods are effective to perform attribute reduction of dynamic covering information systems when attribute sets are varying with time. Copyright © 2017, The Authors. All rights reserved.

关键词： Information use

ROSF: Leveraging Information Retrieval and Supervised Learning for Recommending Code Snippets

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arXiv 2017年

作者： Jiang, He Nie, Liming Sun, Zeyi Ren, Zhilei Kong, Weiqiang Zhang, Tao Luo, Xiapu School of Software Dalian University of Technology Dalian China Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province Dalian China State Key Laboratory of Software Engineering Wuhan University Wuhan China Key Laboratory for Ubiquitous Network Service Software of Liaoning Province Dalian China School of Computer Science & Technology Nanjing University of Posts and Telecommunications Nanjing China Department of Computing Hong Kong Polytechnic University Hong Kong Hong Kong

—when implementing unfamiliar programming tasks, developers commonly search code examples and learn usage patterns of APIs from the code examples or reuse them by copy-pasting and modifying. For providing high-quality code examples, previous studies present several methods to recommend code snippets mainly based on information retrieval. In this paper, to provide better recommendation results, we propose ROSF, Recommending cOde Snippets with multi-aspect Features, a novel method combining both information retrieval and supervised learning. In our method, we recommend Top-K code snippets for a given free-form query based on two stages, i.e., coarse-grained searching and fine-grained re-ranking. First, we generate a code snippet candidate set by searching a code snippet corpus using an information retrieval method. Second, we predict probability values of the code snippets for different relevance scores in the candidate set by the learned prediction model from a training set, re-rank these candidate code snippets according to the probability values, and recommend the final results to developers. We conduct several experiments to evaluate our method in a large-scale corpus containing 921,713 real-world code snippets. The results show that ROSF is an effective method for code snippets recommendation and outperforms the-state-of-the-art methods by 20% - 41% in Precision and 13% - 33% in NDCG. Copyright © 2017, The Authors. All rights reserved.

关键词： Supervised learning

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arXiv 2017年

作者： Lang, Guangming School of Mathematics and Statistics Changsha University of Science and Technology Changsha Hunan410114 China Department of Computer Science and Technology Tongji University Shanghai201804 China The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai201804 China College of Mathematics and Econometrics Hunan University Changsha Hunan410004 China

In practice, there are many dynamic covering decision information systems, and knowledge reduction of dynamic covering decision information systems is a significant challenge of covering-based rough sets. In this paper, we first study mechanisms of constructing attribute reducts for consistent covering decision information systems when adding objects using related families. We also employ examples to illustrate how to construct attribute reducts of consistent covering decision information systems when adding objects. Then we investigate mechanisms of constructing attribute reducts for consistent covering decision information systems when deleting objects using related families. We also employ examples to illustrate how to construct attribute reducts of consistent covering decision information systems when deleting objects. Finally, the experimental results illustrates that the related family-based methods are effective to perform attribute reduction of dynamic covering decision information systems when object sets are varying with time. Copyright © 2017, The Authors. All rights reserved.

关键词： Rough set theory

Behavioral equivalence of security-oriented interactive systems

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Behavioral equivalence of security-oriented interactive syst...

作者： Liu, Guanjun Jiang, Changjun Department of Computer Science Tongji University Shanghai201804 China Key Laboratory of the Ministry of Education for Embedded System and Service Computing Tongji University Shanghai201804 China

In the classical computation theory, the language of a system features the computational behavior of the system but it does not distinguish the determinism and nondeterminism of actions. However, Milner found that the determinism and nondeterminism affect the interactional behavior of interactive systems and thus the notion of language does not features the interactional behavior. Therefore, Milner proposed the notion of (weak) bisimulation to solve this problem. With the development of internet, more and more interactive systems occur in the world, such as electronic trading system. Security is one of the most important topics for these systems. We find that different security policies can also affect the interactional behavior of a system, which exactly is the reason why a good policy can strengthen the security. In other words, two interactive systems with different security policies are not of an equivalent behavior although their functions (or business processes) are identical. However, the classic (weak) bisimulation theory draws an opposite conclusion that their behaviors are equivalent. The notion of (weak) bisimulation is not suitable for these security-oriented interactive systems since it does not consider a security policy. This paper proposes the concept of secure bisimulation in order to solve the above problem. Copyright © 2016 The Institute of Electronics, Information and Communication Engineers.

关键词： Petri nets

Android multi-level system permission management approach

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arXiv 2017年

作者： Luo, Yang Zhang, Qi-Xun Shen, Qing-Ni Liu, Hong-Zhi Wu, Zhong-Hai School of Software and Microelectronics Peking University Beijing100871 China MoE Key Laboratory of Network and Software Assurance Peking University Beijing100871 China Research Laboratory of Service Computing and Big Data Technology Peking University Beijing100871 China

With the expansion of the market share occupied by the Android platform, security issues (especially application security) have become attention focus of researchers. In fact, the existing methods lack the capabilities to manage application permissions without root privilege. This study proposes a dynamic management mechanism of Android application permissions based on security policies. The paper first describes the permissions by security policies, then implementes permission checking code and request evaluation algorithm in Android framework layer. Experimental results indicate that the presented approach succeeds in permission management of Android applications, and its system overhead is low, which makes it an effective method for Android permission management. Copyright © 2017, The Authors. All rights reserved.

关键词： Android (operating system)

DOA and polarization estimation for non-circular signals in 3-D millimeter wave polarized massive MIMO systems

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arXiv 2017年

作者： Wan, Liangtian Liu, Kaihui Liang, Ying-Chang Zhu, Tong Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province School of Software Dalian University of Technology Dalian116620 China National Key Laboratory of Science and Technology on Communications University of Electronic Science and Technology of China Chengdu611731 China National Key Laboratory of Science and Technology on Communications University of Electronic Science and Technology of China Chengdu611731 China School of Electrical and Information Engineering University of Sydney NSW2006 Australia Tianjin Institute of Computing Technology Tianjin300000 China

In this paper, an algorithm of multiple signal classification (MUSIC) is proposed for two-dimensional (2-D) direction-of-arrival (DOA) and polarization estimation of non-circular signal in three-dimensional (3-D) millimeter wave polarized large-scale/massive multiple-input-multiple-output (MIMO) systems. The traditional MUSIC-based algorithms can estimate either the DOA and polarization for circular signal or the DOA for non-circular signal by using spectrum search. By contrast, in the proposed algorithm only the DOA estimation needs spectrum search, and the polarization estimation has a closed-form expression. First, a novel dimension-reduced MUSIC (DR-MUSIC) is proposed for DOA and polarization estimation of circular signal with low computational complexity. Next, based on the quaternion theory, a novel algorithm named quaternion non-circular MUSIC (QNC-MUSIC) is proposed for parameter estimation of non-circular signal with high estimation accuracy. Then based on the DOA estimation result using QNC-MUSIC, the polarization estimation of non-circular signal is acquired by using the closed-form expression of the polarization estimation in DR-MUSIC. In addition, the computational complexity analysis shows that compared with the conventional DOA and polarization estimation algorithms, our proposed QNC-MUSIC and DR-MUSIC have much lower computational complexity, especially when the source number is large. The stochastic Cramér-Rao Bound (CRB) for the estimation of the 2-D DOA and polarization parameters of the non-circular signals is derived as well. Finally, numerical examples are provided to demonstrate that the proposed algorithms can improve the parameter estimation performance when the large-scale/massive MIMO systems are employed. Copyright © 2017, The Authors. All rights reserved.

关键词： MIMO systems

Path Restoring Algorithm based on Vehicle Trajectory Mining

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Path Restoring Algorithm based on Vehicle Trajectory Mining

2016 IEEE International Conference on Big Data Analysis

作者： Yuanhui Sun Yaying Zhang Key Laboratory of Embedded System and Service Computing Tongji University

Path restoring is a path searching problem in the time-dependent road network with the time constraints of origin and destination. This paper proposes a path restoring algorithm to find the possible path that vehicles may have been driving along. We mined the vehicle trajectories based on historical GPS data and then build a "popular" intersection graph based on its entropy and frequency. Then the restoring path is searched on the sub-graph of the popular intersection graph. The experiment result shows that the proposed algorithm increases 10% compared to that of using timedependent fastest path method.

关键词： time-dependent fastest path frequent path footmark graph

Deciphering colorectal cancer genetics through multi-omic analysis of 100,204 cases and 154,587 controls of European and east Asian ancestries (vol 55, pg 89, 2023)

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NATURE GENETICS 2023年第3期55卷 519-520页

作者： Fernandez-Rozadilla, Ceres Timofeeva, Maria Chen, Zhishan Law, Philip Thomas, Minta Schmit, Stephanie Diez-Obrero, Virginia Hsu, Li Fernandez-Tajes, Juan Palles, Claire Sherwood, Kitty Briggs, Sarah Svinti, Victoria Donnelly, Kevin Farrington, Susan Blackmur, James Vaughan-Shaw, Peter Shu, Xiao-ou Long, Jirong Cai, Qiuyin Guo, Xingyi Lu, Yingchang Broderick, Peter Studd, James Huyghe, Jeroen Harrison, Tabitha Conti, David Dampier, Christopher Devall, Mathew Schumacher, Fredrick Melas, Marilena Rennert, Gad Obon-Santacana, Mireia Martin-Sanchez, Vicente Moratalla-Navarro, Ferran Oh, Jae Hwan Kim, Jeongseon Jee, Sun Ha Jung, Keum Ji Kweon, Sun-Seog Shin, Min-Ho Shin, Aesun Ahn, Yoon-Ok Kim, Dong-Hyun Oze, Isao Wen, Wanqing Matsuo, Keitaro Matsuda, Koichi Tanikawa, Chizu Ren, Zefang Gao, Yu-Tang Jia, Wei-Hua Hopper, John Jenkins, Mark Win, Aung Ko Pai, Rish Figueiredo, Jane Haile, Robert Gallinger, Steven Woods, Michael Newcomb, Polly Duggan, David Cheadle, Jeremy Kaplan, Richard Maughan, Timothy Kerr, Rachel Kerr, David Kirac, Iva Bohm, Jan Mecklin, Lukka-Pekka Jousilahti, Pekka Knekt, Paul Aaltonen, Lauri Rissanen, Harri Pukkala, Eero Eriksson, Johan Cajuso, Tatiana Hanninen, Ulrika Kondelin, Johanna Palin, Kimmo Tanskanen, Tomas Renkonen-Sinisalo, Laura Zanke, Brent Mannisto, Satu Albanes, Demetrius Weinstein, Stephanie Ruiz-Narvaez, Edward Palmer, Julie Buchanan, Daniel Platz, Elizabeth Visvanathan, Kala Ulrich, Cornelia Siegel, Erin Brezina, Stefanie Gsur, Andrea Campbell, Peter Chang-Claude, Jenny Hoffmeister, Michael Brenner, Hermann Slattery, Martha Potter, John Tsilidis, Konstantinos Schulze, Matthias Gunter, Marc Murphy, Neil Castells, Antoni Castellvi-Bel, Sergi Moreira, Leticia Arndt, Volker Shcherbina, Anna Stern, Mariana Pardamean, Bens Bishop, Timothy Giles, Graham Southey, Melissa Idos, Gregory McDonnell, Kevin Abu-Ful, Zomoroda Greenson, Joel Shulman, Katerina Lejbkowicz, Flavio Offit, Kenneth Su, Yu-Ru Steinfelder, Robert Keku, Temitope van Guelpen, Bethany Hudson, Thomas Hampel, Heather Pearlman, Edinburgh Cancer Research Centre Institute of Genomics and Cancer University of Edinburgh Edinburgh UK Genomic Medicine Group Instituto de Investigacion Sanitaria de Santiago Santiago de Compostela Spain Colon Cancer Genetics Group Medical Research Council Human Genetics Unit Institute of Genetics and Cancer University of Edinburgh Edinburgh UK Danish Institute for Advanced Study Department of Public Health University of Southern Denmark Odense Denmark Division of Epidemiology Department of Medicine Vanderbilt-Ingram Cancer Center Vanderbilt Epidemiology Center Vanderbilt University Medical Center Nashville TN USA Division of Genetics and Epidemiology Institute of Cancer Research London UK Public Health Sciences Division Fred Hutchinson Cancer Research Center Seattle WA USA Genomic Medicine Institute Cleveland Clinic Cleveland OH USA Population and Cancer Prevention Program Case Comprehensive Cancer Center Cleveland OH USA Colorectal Cancer Group ONCOBELL Program Bellvitge Biomedical Research Institute Barcelona Spain Oncology Data Analytics Program Catalan Institute of Oncology Barcelona Spain Consortium for Biomedical Research in Epidemiology and Public Health Madrid Madrid Spain Department of Clinical Sciences Faculty of Medicine University of Barcelona Barcelona Spain Department of Biostatistics School of Public Health University of Washington Seattle WA USA Institute of Cancer and Genomic Sciences College of Medical and Dental Sciences University of Birmingham Birmingham UK Department of Public Health Richard Doll Building University of Oxford Oxford UK Department of Biomedical Informatics Vanderbilt University School of Medicine Nashville TN USA Department of Preventive Medicine USC Norris Comprehensive Cancer Center Keck School of Medicine University of Southern California Los Angeles CA USA Center for Public Health Genomics Department of Public Health Sciences University of Virginia Charlottesville VA USA Department of Populat

Colorectal cancer (CRC) is a leading cause of mortality worldwide. We conducted a genome-wide association study meta-analysis of 100,204 CRC cases and 154,587 controls of European and east Asian ancestry, identifying 205 independent risk associations, of which 50 were unreported. We performed integrative genomic, transcriptomic and methylomic analyses across large bowel mucosa and other tissues. Transcriptome- and methylome-wide association studies revealed an additional 53 risk associations. We identified 155 high-confidence effector genes functionally linked to CRC risk, many of which had no previously established role in CRC. These have multiple different functions and specifically indicate that variation in normal colorectal homeostasis, proliferation, cell adhesion, migration, immunity and microbial interactions determines CRC risk. Crosstissue analyses indicated that over a third of effector genes most probably act outside the colonic mucosa. Our findings provide insights into colorectal oncogenesis and highlight potential targets across tissues for new CRC treatment and chemoprevention strategies.

关键词： Colorectal cancer Epigenomics Genome-wide association studies Transcriptomics

JOINT DETECTION AND CLINICAL SCORE PREDICTION IN PARKINSON'S DISEASE VIA MULTI-MODAL SPARSE LEARNING

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JOINT DETECTION AND CLINICAL SCORE PREDICTION IN PARKINSON'S...

International Symposium on Biomedical Imaging

作者： Haijun Lei Jian Zhang Zhang Yang Ee-leng Tan Baiying Lei Qiuming Luo College of Computer Science and Software Engineering Shenzhen University Key Laboratory of Service Computing and Applications Guangdong Province Key Laboratory of Popular High Performance Computers School of Information Engineering Shenzhen University School of Electric and Electronic Engineering Nanyang Technological University School of Biomedical Engineering Shenzhen University Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging National-Regional Key Technology Engineering Laboratory for Medical Ultrasound

ISBN: (纸本)9781509011735

In this study, a novel feature selection framework is proposed to simultaneously perform classification and clinical scores prediction of Parkinson's disease (PD) via multi-modal neuroimaging data. Specifically, a new feature selection model is devised to capture discriminative features to train support vector regression model for clinical scores (e.g., sleep scores and olfactory scores) prediction and support vector classification model for class label identification. Our method is evaluated on a public dataset of 208 subjects including 56 normal controls (NC), 123 PD and 29 scans without evidence of dopamine deficit (SWEDD) via a 10-fold cross-validation method. The experimental results demonstrate that multimodal data can effectively improve the performance in disease status identification and clinical scores prediction compared to one single modality. Our proposed method also outperforms the related methods.

关键词： Parkinson's disease Feature selection Classification Prediction Multi-modal data