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11th International Conference on Ubiquitous information Management and Communication, IMCOM 2017

作者： Gao, Xiaofeng Dang, Yaru Chen, Guihai Gu, Jian Wang, Yongjian Shanghai Key Lab of Scalable Computing and Systems Dept. of Computer Science Shanghai Jiao Tong University Shanghai China Civil Aviation SandT Educational Evaluation Research Center Civil Aviation University of China Tianjin China Key Laboratory of Information Network Security Ministry of Public Security Third Research Institute of Ministry of Public Security Shanghai China

ISBN: (纸本)9781450348881

In this paper we study the survivability feature of airline networks. To measure survivability, we comprehensively consider the network structure measures such as degree distribution, average path length, clustering coefficient, and density;the centrality metrics such as degree centrality and betweenness centrality;as well as the connectivity measures such as maximum connected subgraph size and overall efficiency. Taking three listed China airline companies as examples, namely Air China, China Southern Airlines, and China Eastern Airlines, we provide mass number of simulations to test the survivability of the three companies under random attacks and malicious attacks. The results depict the scalefree features of such networks without small-world characteristics, while the attack simulations reflect the survivability of airline networks clearly. To the best of our knowledge, we are the first to provide case studies for airline networks of individual airline companies in China, which has both theoretical and practical significance in related areas. © 2017 ACM.

关键词： Complex networks

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From retweet to believability: Utilizing trust to identify rumor spreaders on twitter 9

From retweet to believability: Utilizing trust to identify r...

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9th IEEE/ACM International Conference on Advances in Social networks Analysis and Mining, ASONAM 2017

作者： Rath, Bhavtosh Gao, Wei Ma, Jing Srivastava, Jaideep Dept. Of Computer Science and Engineering University of Minnesota Twin CitiesMN United States School of Information Management Victoria University of Wellington Wellington New Zealand Dept. Of Systems Engineering and Engineering Management Chinese University of Hong Kong Hong Kong Qatar Computing Research Institute Doha Qatar

ISBN: (纸本)9781450349932

Ubiquitous use of social media such as microblog-ging platforms brings about ample opportunities for the false information to diffuse online. It is very important not just to determine the veracity of information but also the authenticity of the users who spread the information, especially in time-critical situations like real-world emergencies, where urgent measures have to be taken for stopping the spread of fake information. In this work, we propose a novel machine learning based approach for automatic identification of the users spreading rumorous information by leveraging the concept of believability, i.e., the extent to which the propagated information is likely to be perceived as truthful, based on the trust measures of users in Twitter’s retweet network. We hypothesize that the believability between two users is proportional to the trustingness of the retweeter and the trustworthiness of the tweeter, which are two complementary measures of user trust and can be inferred from retweeting behaviors using a variant of HITS algorithm. With the retweet network edge-weighted by believability scores, we use network representation learning to generate user embeddings, which are then leveraged to classify users into as rumor spreaders or not. Based on experiments on a very large real-world rumor dataset collected from Twitter, we demonstrate that our method can effectively identify rumor spreaders and outperform four strong baselines with large margin. © 2017 Association for Computing Machinery.

关键词： Spreaders

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Web-Based Application to Collect and Analyze Users Data for Keystroke Biometric Authentication

Web-Based Application to Collect and Analyze Users Data for ...

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IEEE Ukraine Conference on Electrical and computer engineering

作者： Alieksieiev Vasyl Elena Sharapova Olena Ivanova Gorelov Denis Synytsia Yuliia Computer Radio Engineering and Systems of Technical Security of Information dept.(CRESTSI) Kharkiv National University of Radioelectronics (KNURE) Software Engineering Dept. Marvell Semiconductor Inc.

ISBN: (纸本)9781509030071

Keystroke dynamics is rapidly developing and promising field of the research. User authentication systems based on this approach is not require the installation of additional equipment. It makes them flexible and significantly reduces the cost of implementation and subsequent exploitation. This paper describes the web application developed to collect and analyze individual characteristics of user keystroke based on time calculation of digraphs. That approach has several advantages such as simplicity to use, ability to obtain data at any time, to integrate application into an existing web resource, application is cross platform, has modular architecture and provide great scalability.

关键词： Web application Authentication Keystroke dynamics Data collection Digraph Modularity Cross platform

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Abstracts

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JOURNAL OF SPINAL CORD MEDICINE 2021年第SUPPL 1期44卷 S278-S324页

作者： [Anonymous] Department of Medicine Division of Physical Medicine and Rehabilitation University of Toronto Toronto ON CA KITE - Toronto Rehabilitation Institute University Health Network Toronto ON CA Institute for Health Policy Management and Evaluation University of Toronto Toronto ON CA Rehabilitation Sciences Institute University of Toronto Toronto ON CA Institute of Medical Sciences University of Toronto Toronto ON CA. Rehabilitation Sciences Institute University of Toronto ON CA KITE Research Institute-Toronto Rehab-University Health Network Toronto ON CA Physical Therapy Department University of Toronto ON CA Praxis Spinal Cord Institute Vancouver BC Université de Montréal (École de réadaptation) Montreal QC CA Institut de réadaptation Gingras-Linsay-de-Montréal Montreal QC CA Division of Physical Medicine & Rehabilitation Department of Medicine Faculty of Medicine & Dentistry University of Alberta Edmonton AB CA University of Calgary Calgary AB CA Alberta Health Services Centre for Family Medicine Kitchener ON CA McMaster University Department of Family Medicine Hamilton ON CA Dept. of Physical Therapy University of Toronto Toronto ON CA KITE-University Health Network Toronto ON CA Praxis Spinal Cord Institute Vancouver BC CA Center for Interdisciplinary Research in Rehabilitation and Social Integration (CIRRIS) Quebec City QC CA Dept. of Rehabilitation Laval University Quebec City QC CA Institute of Health Policy Management and Evaluation University of Toronto Toronto ON CA School of Rehabilitation Science University of Saskatchewan Saskatoon SK CA Ontario Neurotrauma Foundation Toronto ON CA Canadian Spinal Research Organization Toronto ON CA CIUSSS du Centre-Sud-de-l ‘Île-de-Montréal (Installation Gingras-Lindsay) Montréal QC CA École de réadaptation Université de Montréal Montréal QC CA First Steps Wellness Centre Regina SK CA Stan Cassidy Centre for Rehabilitation Horizon Health Network Fredericton NB CA Departmen

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A joint network/control design for cooperative automatic driving

A joint network/control design for cooperative automatic dri...

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2017 IEEE Vehicular networking Conference, VNC 2017

作者： Giordano, Giulia Segata, Michele Blanchini, Franco Cigno, Renato Lo Delft Center for Systems and Control Delft University of Technology Netherlands Dipartimento di Matematica e Informatica University of Udine Italy Dept. of Information Engineering and Computer Science University of Trento Italy

ISBN: (纸本)9781538609866

Cooperative automatic driving, or platooning, is a promising solution to improve traffic safety, while reducing congestion and pollution. The design of a control system for this application is a challenging, multi-disciplinary problem, as cooperation between vehicles is obtained through wireless communication. So far, control and network issues of platooning have been investigated separately. In this work we design a cooperative driving system from a joint network and control perspective, determining worst-case upper bounds on the safety distance subject to network losses, so the actual inter-vehicle gap can be tuned depending on vehicle or network performance. By means of simulation, we show that the system is very robust to packet losses and that the derived bounds are never violated. © 2017 IEEE.

关键词： Traffic congestion

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Baggage detection and classification using human body parameter & boosting technique

Baggage detection and classification using human body parame...

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Conference on Human System Interactions, HSI

作者： Tahmina Khanam Kaushik Deb Kang-Hyun Jo Dept. of Computer Science & Engineering Chittagong University of Engineering & Technology Chittagong Bangladesh Dept. of EE and Information Systems University of Ulsan Ulsan Korea

ISBN: (纸本)9781509056132

Automatic Video Surveillance System (AVSS) has become important to computer vision researchers as crime in public places has increased in the twenty first century. As a new branch of AVSS, baggage detection and classification has a broad area of security applications. Some of them are, detecting carriage of illegal materials into baggage, detecting unclaimed baggage in public space that can be placed by terrorists for violence, detecting baggage in baggage restricted super shop etc. However, in this paper, a detection & classification framework of baggage is proposed using dynamic human body parameter with boosting strategy. Initially, background subtraction is performed instead of sliding window approach to speed up the system and HSI model is used to deal with uneven illumination condition. Then, to overcome the shadow effect a model is introduced. Extraction of rotational signal descriptor (RSD_HOG) from Region of Interest (ROI) added efficiency in HOG. Finally, dynamic approach in human body parameter setting enabled the system to detect & classify single or multiple carried baggages although some portions of human are absent. In baggage detection, boosting of similarity measure based cascade multilayer SVMs into HOG based SVM generated a strong classifier. This scheme has used to deal with various texture patterns of baggages. Experimental results discovered the system satisfactorily accurate and faster comparative to other alternatives.

关键词： Feature extraction Boosting Support vector machines Lighting Biological system modeling Nonhomogeneous media information filtering

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Heterogeneity of human brain tumor with lesion identification, localization, and analysis from MRI

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Informatics in Medicine Unlocked 2019年 16卷

作者： Sudipta Roy Debnath Bhattacharyya Samir Kumar Bandyopadhyay Tai-Hoon Kim Washington University in St. Louis Dept. of Comp. Sc. & Engg. Saint Louis Missouri 63110 USA Department of Computer Science and Engineering Vignan's Institute of Information Technology Visakhapatnam 530049 India Department of Computer Science and Engineering Calcutta University Technology Campus Kolkata 700098 India Department of Convergence Security Sungshin Women's University Seoul 136-742 South Korea

Objective Accurate identification of brain tumors and their heterogeneity is a critical task in planning for proper therapy. A reliable fully automatic detection and analysis method for the brain tumor is necessary for an efficient measurement of the tumors and their extent. This paper presents a computerized approach to brain tumor-edema detection and analysis from the MRI of brain sequences. Method computer-aided diagnosis systems are focused on several research activities, and the ideas of the study of brain images with the diverse modality of heterogeneity by applying better image analysis algorithms. The proposed automated modern approach includes several stages of image segmentation, area and volume calculation, and locational findings using statistical and an unsupervised clustering prediction method. Result The outcome of the proposed computerized method is compared with reference images and gives very promising results. Performance of our proposed methodology is also assessed with the gold standard recent comparable method, and our method gives better results in the context of accuracy and error metrics. Conclusion The proposed method is capable of improving the overall detection, segmentation, and quantification of a variety of tumors for different cases from multiple standard datasets.

关键词： Abnormality detection Brain tumor Segmentation Heterogeneity Magnetic resonance imaging Accuracy estimation

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LigeroAV: A light-weight, signature-based antivirus for mobile environment

LigeroAV: A light-weight, signature-based antivirus for mobi...

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作者： Lee, Jaehwan Jo, Min Jae Shin, Ji Sun Dept. of Electronics and Information Engineering Korea Aerospace University Goyang-city10540 Korea Republic of Dept. of Computer and Information Security Sejong University Seoul05006 Korea Republic of

Current signature-based antivirus solutions have three limitations such as the large volume of signature database, privacy preservation, and computation overheads of signature matching. In this paper, we propose LigeroAV, a light-weight, performance-enhanced antivirus, suitable for pervasive environments such as mobile phones. LigeroAV focuses on detectingMD5 signatures which are more than 90% of signatures. LigeroAV offloads matching computation in the cloud server with up-todated signature database while preserving privacy level using the Bloom filter. © Copyright 2016 The Institute of Electronics, information and Communication Engineers.

关键词： Bandpass filters

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Multiple influence maximization in social networks 10

Multiple influence maximization in social networks

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10th International Conference on Ubiquitous information Management and Communication, IMCOM 2016

作者： Sun, Honglin Gao, Xiaofeng Chen, Guihai Gu, Jian Wang, Yongjian Shanghai Key Lab. of Scalable Computing and Systems Dept. of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China Key Laboratory of Information Network Security of Ministry of Public Security Third Research Institute of Ministry of Public Security Shanghai China

ISBN: (纸本)9781450341424

Influence Maximization, a technique of social analysis to help marketers select a small group of users to promote their products with the goal of maximizing their influence spread, has been studied for a long time. However, previous researches did not consider the scenario that a company may intend to promote serval kinds of products in the same social network, where each user has different preferences for different categories. Considering this scenario in this paper, we propose the Multiple Influence Maximization (MIM) problem based on the assumption that one seed user can accept serval kinds of goods for free, and at the same time non-seed users have enough purchasing power to accept different promotions from their social friends. To address this issue, we design the corresponding greedy algorithm framework with an approximate radio of 1-1/e if the influence function is submodular. Besides, to simplify the computation of influence spread and considering the properties of real social influence propagation, we propose a novel influence quantitative computation model in which influence function fortunately is submodular. Applying this model into our MIM problem, the experiment results show that the greedy algorithm out-performs serval traditional heuristics in influence spread without loss of performance. © 2015 ACM.

关键词： Method of moments

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A framework for OpenFlow-like Policy-based routing in hybrid software defined networks 11

A framework for OpenFlow-like Policy-based routing in hybrid...

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11th International network Conference, INC 2016

作者： Mishra, Anshuman Bansod, Deven Haribabu, K. Dept. of Electrical and Electronics Engineering Birla Institute of Technology and Science Pilani India Dept. of Computer Science and Information Systems Birla Institute of Technology and Science Pilani India

ISBN: (纸本)9781841024103

Software Defined networks (SDNs) provide a centralized view and allow extensive programmability of the network. They separate the control and data planes opening up immense scope in developing low cost control and management applications to operate the network. Yet, network administrators are ambivalent to revamp their entire network hardware to bring in SDN-compatible switches. This leads to the need for developing models for gradual adaptation of SDN technology. In this paper, we present a framework which allows for policy implementations based on all OpenFlow version 1.4 specified match fields, over legacy Layer 3 devices. This would enable the legacy networks to reap the benefits of SDN in an incremental, controlled and consistent manner.

关键词： Software defined networking

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