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Annual ACM-Society for Industrial and Applied Mathmatics Symposium on Discrete Algorithms

作者： Sunil Arya David M. Mount Dept. of Computer Science and Engineering The Hong Kong University of Science and Technology Dept. of Computer Science and Inst. for Advanced Computer Studies University of Maryland

ISBN: (纸本)9781510819672

The Euclidean minimum spanning tree (EMST) is a fundamental and widely studied structure. In the approximate version we are given an n-element point set P in Rd and an error parameter ε > 0, and the objective is to compute a spanning tree over P whose weight is at most (1 + ε) times that of the true minimum spanning tree. Assuming that d is a fixed constant, existing algorithms have running times that (up to logarithmic factors) grow as O(n/ε~(Ω(d))). We present an algorithm whose running time is O(n log n+(ε~(-2) log~2 1/ε)n). Thus, this is the first algorithm for approximate EMSTs that eliminates the exponential ε dependence on dimension. (Note that the O-notation conceals a constant factor of the form O(1)~d.) The algorithm is deterministic and very simple.

关键词： Euclidean minimum spanning trees Well-separated pair decompositions Approximation algorithms Approximation algorithms Spanning tree Runtime algorithms Euclidean Approximate minimum error parameter

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Utilization of hybrid access femtocells during multicast transmissions in mobile networks

Utilization of hybrid access femtocells during multicast tra...

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European Conference on Networks and Communications (EuCNC)

作者： Christos Bouras Nikolaos Kanakis Vasileios Kokkinos Nikolaos Papachristos Demosthenes Vouyioukas Computer Engineering and Informatics Dept. Univ. of Patras Greece Computer Technology Institute & Press “Diophantus” Patras Greece Dept. of Information & Communication System Engineering Univ. of Aegean Greece

ISBN: (纸本)9781509028948

Femtocells enhance indoor coverage of mobile services using the owner's broadband connection. They were initially designed to serve a number of subscribed User Equipments within their range. This design however, resulted in underutilization of the femtocells resources, and simultaneously in high interference levels for nearby non-subscribed users. Nowadays, femtocells can support multicast transmissions, while their hybrid operation allows non-subscribed users to use a portion of their resources. In this paper we propose a novel mechanism that is based on the selection of the appropriate Modulation and Coding Scheme. The mechanism allows non-subscribed users to utilize a portion of the femtocells' resources for multicast transmissions when located inside their coverage, without affecting the owners' satisfaction. The simulation results show that depending on the portion of the femtocells' resources allocated to non-subscribed users, the mechanism may significantly increase the average user throughput.

关键词： Femtocells Throughput Interference Signal to noise ratio Macrocell networks Encoding

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Energy efficient context based forwarding strategy in named data networking of things 3

Energy efficient context based forwarding strategy in named ...

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3rd ACM International Conference on Information-Centric Networking, ACM-ICN 2016

作者： Lenord Melvix, J.S.M. Lokesh, Vikas Polyzos, George C. Dept. of Computer Science and Engineering Jacobs School of Engineering University of California San Diego San DiegoCA92093-0114 United States Mobile Multimedia Lab Dept. of Informatics School of Information Sciences and Technology Athens University of Economics and Business Evelpidon 47A Athens113 62 Greece

ISBN: (纸本)9781450344678

Named Data Networking (NDN) of Things has gathered interest among the Internet-of-Things (IoT) research community due to its hassle-free deployment and configurability. This approach to interconnecting devices provides the network with additional information about the data transported, which can be used for improved efficiency. This is one of the targets for mass IoT or Machine-to-Machine (M2M) communications modes of 5G. In this paper, we propose a context based forwarding strategy that makes forwarding decisions based on the tolerance to inaccuracies in data defined for the application requesting it. We also propose a modification to the hierarchical naming scheme by appending the name of the application generating the interest. In addition to faster context based forwarding, this modification simplifies the naming as it is easier to understand the context under which the interest was generated even with generic names. We demonstrate an improvement in energy efficiency of the system using the proposed technique compared to an IP based implementation. In addition, the proposed technique offers a platform to implement application level access control and Quality-of-Service support. ©2016 ACM.

关键词： Middleware

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Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge

arXiv

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arXiv 2018年

作者： Bakas, Spyridon Reyes, Mauricio Jakab, Andras Bauer, Stefan Rempfler, Markus Crimi, Alessandro Shinohara, Russell Takeshi Berger, Christoph Ha, Sung Min Rozycki, Martin Prastawa, Marcel Alberts, Esther Lipkova, Jana Freymann, John Kirby, Justin Bilello, Michel Fathallah-Shaykh, Hassan M. Wiest, Roland Kirschke, Jan Wiestler, Benedikt Colen, Rivka Kotrotsou, Aikaterini Lamontagne, Pamela Marcus, Daniel Milchenko, Mikhail Nazeri, Arash Weber, Marc-Andr Mahajan, Abhishek Baid, Ujjwal Gerstner, Elizabeth Kwon, Dongjin Acharya, Gagan Agarwal, Manu Alam, Mahbubul Albiol, Alberto Albiol, Antonio Albiol, Francisco J. Alex, Varghese Allinson, Nigel Amorim, Pedro H.A. Amrutkar, Abhijit Anand, Ganesh Andermatt, Simon Arbel, Tal Arbelaez, Pablo Avery, Aaron Azmat, Muneeza Pranjal, B. Bai, Wenjia Banerjee, Subhashis Barth, Bill Batchelder, Thomas Batmanghelich, Kayhan Battistella, Enzo Beers, Andrew Belyaev, Mikhail Bendszus, Martin Benson, Eze Bernal, Jose Bharath, Halandur Nagaraja Biros, George Bisdas, Sotirios Brown, James Cabezas, Mariano Cao, Shilei Cardoso, Jorge M. Carver, Eric N. Casamitjana, Adri Castillo, Laura Silvana Cat, Marcel Cattin, Philippe Cérigues, Albert Chagas, Vinicius S. Chandra, Siddhartha Chang, Yi-Ju Chang, Shiyu Chang, Ken Chazalon, Joseph Chen, Shengcong Chen, Wei Chen, Jefferson W. Chen, Zhaolin Cheng, Kun Choudhury, Ahana Roy Chylla, Roger Clrigues, Albert Colleman, Steven Colmeiro, Ramiro German Rodriguez Combalia, Marc Costa, Anthony Cui, Xiaomeng Dai, Zhenzhen Dai, Lutao Daza, Laura Alexandra Deutsch, Eric Ding, Changxing Dong, Chao Dong, Shidu Dudzik, Wojciech Eaton-Rosen, Zach Egan, Gary Escudero, Guilherme Estienne, Tho Everson, Richard Fabrizio, Jonathan Fan, Yong Fang, Longwei Feng, Xue Ferrante, Enzo Fidon, Lucas Fischer, Martin French, Andrew P. Fridman, Naomi Fu, Huan Fuentes, David Gao, Yaozong Gates, Evan Gering, David Gholami, Amir Gierke, Willi Glocker, Ben Gong, Mingming Gonzlez-Vill, Sandra Grosges, T. Guan, Yuanfang Guo, Sheng Gupta, Sudeep Han, Woo-Sup Han, Il Song Harmuth, Ko Center for Biomedical Image Computing and Analytics University of Pennsylvania PhiladelphiaPA United States Department of Radiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Institute for Surgical Technology and Biomechanics University of Bern Bern Switzerland Center for MR-Research University Children's Hospital Zurich Zurich Switzerland Support Centre for Advanced Neuroimaging Inselspital Institute for Diagnostic and Interventional Neuroradiology Bern University Hospital Bern Switzerland University Hospital of Zurich Zurich Switzerland Center for Clinical Epidemiology and Biostatistics University of Pennsylvania Philadelphia United States Image-Based Biomedical Modeling Group Technical University of Munich Munich Germany Icahn School of Medicine Mount Sinai Health System New YorkNY United States Leidos Biomedical Research Inc. Frederick National Laboratory for Cancer Research FrederickMD21701 United States Cancer Imaging Program National Cancer Institute National Institutes of Health BethesdaMD20814 United States Department of Neurology University of Alabama at Birmingham BirminghamAL United States Department of Diagnostic Radiology University of Texas MD Anderson Cancer Center HoustonTX United States Department of Psychology Washington University St. LouisMO United States Neuroimaging Informatics and Analysis Center Washington University St. LouisMO United States Department of Radiology Washington University St. LouisMO United States Institute of Diagnostic and Interventional Radiology Pediatric Radiology and Neuroradiology University Medical Center Rostock Ernst-Heydemann-Str. 6 Rostock18057 Germany Tata Memorial Centre Homi Bhabha National Institute Mumbai India Shri Guru Gobind Singhji Institute of Engineering and Technology Nanded India NVIDIA Santa Clara

Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and non-enhancing core. This intrinsic heterogeneity is also portrayed in their radio-phenotype, as their sub-regions are depicted by varying intensity profiles disseminated across multi-parametric magnetic resonance imaging (mpMRI) scans, reflecting varying biological properties. Their heterogeneous shape, extent, and location are some of the factors that make these tumors difficult to resect, and in some cases inoperable. The amount of resected tumor is a factor also considered in longitudinal scans, when evaluating the apparent tumor for potential diagnosis of progression. Furthermore, there is mounting evidence that accurate segmentation of the various tumor sub-regions can offer the basis for quantitative image analysis towards prediction of patient overall survival. This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i.e., 2012-2018. Specifically, we focus on i) evaluating segmentations of the various glioma sub-regions in pre-operative mpMRI scans, ii) assessing potential tumor progression by virtue of longitudinal growth of tumor sub-regions, beyond use of the RECIST/RANO criteria, and iii) predicting the overall survival from pre-operative mpMRI scans of patients that underwent gross total resection. Finally, we investigate the challenge of identifying the best ML algorithms for each of these tasks, considering that apart from being diverse on each instance of the challenge, the multi-institutional mpMRI BraTS dataset has also been a continuously evolving/growing dataset. Copyright © 2018, The Authors. All rights reserved.

关键词： Tumors

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SemEval-2016 task 5: Aspect based sentiment analysis 10

SemEval-2016 task 5: Aspect based sentiment analysis

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10th International Workshop on Semantic Evaluation, SemEval 2016

作者： Pontiki, Maria Galanis, Dimitrios Papageorgiou, Haris Androutsopoulos, Ion Manandhar, Suresh Al-Smadi, Mohammad Al-Ayyoub, Mahmoud Zhao, Yanyan Qin, Bing De Clercq, Orphée Hoste, Véronique Apidianaki, Marianna Tannier, Xavier Loukachevitch, Natalia Kotelnikov, Evgeny Bel, Nuria Jiménez-Zafra, Salud María Eryigit, Gülsen Institute for Language and Speech Processing Athena R.C. Athens Greece Dept. of Informatics Athens University of Economics and Business Greece Dept. of Computer Science University of York United Kingdom Computer Science Dept. Jordan University of Science and Technology Irbid Jordan Harbin Institute of Technology Harbin Heilongjiang China LT3 Ghent University Ghent Belgium LIMSI CNRS Univ. Paris-Sud Université Paris-Saclay Orsay France Lomonosov Moscow State University Moscow Russia Vyatka State University Kirov Russia Universitat Pompeu Fabra Barcelona Spain Dept. of Computer Science Universidad de Jaén Spain Dept. of Computer Engineering Istanbul Technical University Turkey

ISBN: (纸本)9781941643952

This paper describes the SemEval 2016 shared task on Aspect Based Sentiment Analysis (ABSA), a continuation of the respective tasks of 2014 and 2015. In its third year, the task provided 19 training and 20 testing datasets for 8 languages and 7 domains, as well as a common evaluation procedure. From these datasets, 25 were for sentence-level and 14 for text-level ABSA;the latter was introduced for the first time as a subtask in SemEval. The task attracted 245 submissions from 29 teams. © 2016 Association for Computational Linguistics.

关键词： Sentiment analysis

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Preventing DOS & MITM Attacks in “anonymous location based efficient routing protocol” in MANET

Preventing DOS & MITM Attacks in “anonymous location based ...

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IEEE International Conference on engineering and technology (ICETECH)

作者： Priyanka Patil Nilesh Marathe Vimla Jethani Dept. of Computer Engineering Ramrao Adik Inst. of Technology Navi Mumbai India

ISBN: (纸本)9781467399159

Mobile Ad Hoc Networks (MANETs) gained lot of importance due to fast growth of the businesses and used in different applications such as military, entertainment, commerce, emergency services etc. Because of openness and decentralization feature of the MANET, nodes of the MANET can be vulnerable to malicious entities. Hence, anonymity becomes one of the important aspects in MANET. In last few years, a lot of research has been carried out by different researcher to prevent the anonymity of the MANET. Different routing protocols have been evolved such as GSPR, AO2P, ALARM, PRISM and ASR to secure the anonymity of the MANET. But all of these protocols have some limitations regarding providing complete anonymity of source, destination or routes and also involving high cost. To overcome above issues ALERT protocol is evolved which is distinguished by its low cost and anonymity protection for sources, destinations, and routes. But ALERT protocol is not providing security against the active attacks, so in the proposed work we have decided to make the strategy to prevent the DoS and Man in the middle attacks on ALERT by using Hash function with SHA-1 algorithm.

关键词： Routing protocols Mobile ad hoc networks Routing Security Receivers computers

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Improved ALERT protocol in MANET with strategies to prevent DOS & MITM attacks

Improved ALERT protocol in MANET with strategies to prevent ...

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International Conference on Automatic Control and Dynamic Optimization Techniques (ICACDOT)

作者： Priyanka Patil Nilesh Marathe Vimla Jethani Dept. of Computer Engineering Ramrao Adik Inst. of Technology Nerul Navi Mumbai India

ISBN: (纸本)9781509020812

Mobile Ad Hoc Networks (MANETs) gained lot of importance due to fast growth of the businesses and used in different applications such as military, entertainment, commerce, emergency services etc. Because of openness and decentralization feature of the MANET, nodes of the MANET can be vulnerable to malicious entities. Hence, anonymity becomes one of the important aspects in MANET. In last few years, a lot of research has been carried out by different researcher to prevent the anonymity of the MANET. Different routing protocols have been evolved such as ANODR, GSPR, AO2P, ALARM and ASR to secure the anonymity of the MANET. But all of these protocols have some limitations regarding providing complete anonymity of source, destination and also routes and also involving high cost due to hop by hop encryption and redundant traffic. To overcome above issues ALERT protocol is evolved which is distinguished by its low cost due to randomized routing mechanism and anonymity protection for sources, destinations, and routes. But ALERT protocol does not have any strategy to provide security against the active attacks such as MITM and DoS attack. So in the proposed work we have designed new strategy which uses hashing with SHA-1 algorithm and location based pseudonyms of nodes technique to avoid the attacks. The simulation of the existing and proposed ALERT protocol has been carried out with JAVA using JUNG tools and shown that our proposed solution is able to avoid the attacks on the network. Also it is efficient in terms of energy consumption and packet delivery ratio as compared to existing ALERT protocol.

关键词： Mobile ad hoc networks Routing protocols Routing Encryption Receivers

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Real-time 3D tumor tracking based on 2D projections of implanted markers 31

Real-time 3D tumor tracking based on 2D projections of impla...

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31st International Conference on computers and Their Applications, CATA 2016

作者： Mao, Songan Wu, Huanmei Lu, Minghui Cheng, Chee-Wai Dept. of Electrical and Computer Engineering Purdue University IndianapolisIN46202 United States School of Engineering and Technology IUPUI School of Informatics and Computing IUPUI IndianapolisIN46202 United States PerkinElmer Medical Imaging Inc. Santa ClaraCA95054 United States UH Case Medical Center 11100 Euclid Ave ClevelandOH44106 United States

ISBN: (纸本)9781943436026

In cancer radiation therapy, the treatment effectiveness is degraded greatly by the tumor respiratory motion during treatment delivery, induced by patient free breathing and organ motions. Advance treatment delivery techniques with image guidance helps to address the tumor motion challenges. However, real-time tumor localization is still a big concern as the respiratory motion dynamically changes its motion velocities, directions, and amplitude during treatment delivery. In this project, an optimized internal marker 3D localization method was proposed by combining the use of onboard kiovoltage (kV) beam and megavoltage (MV) imaging systems. Two sets of 2D projection images from any pair of kV-kV, kV-MV or MV-MV with different gantry rotation angles will be utilized to derive the 3D tumor positions. This approach transforms the projection 2D images to the original 3D location without requirements of the two imaging systems to be orthogonal. The accuracy of the proposed method was validated by several evaluation metrics. The average 3D Euclidean difference is between 0.21 mm to 0.56 mm, which is within the range of clinical applications. Further study will be carried out to evaluate the system comprehensively and integrate to the existing treatment delivery system for better communications among different systems. It potentially will improve the treatment accuracy and provide better health care to cancer patients. Copyright ISCA.

关键词： Tumors

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An Ontology-based contextual pre-filtering technique for Recommender Systems

An Ontology-based contextual pre-filtering technique for Rec...

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Federated Conference on computer Science and Information Systems (FedCSIS)

作者： Aleksandra Karpus Iacopo Vagliano Krzysztof Goczyła Maurizio Morisio Faculty of Electronics Telecommunication and Informatics Gdansk University of Technology Gdańsk-Wrzeszcz Poland Dept. Control and Computer Engineering Politecnico di Torino Turin Italy

Context-aware Recommender Systems aim to provide users with the most adequate recommendations for their current situation. However, an exact context obtained from a user could be too specific and may not have enough data for accurate rating prediction. This is known as the data sparsity problem. Moreover, often user preference representation depends on the domain or the specific recommendation approach used. Therefore, a big effort is required to change the method used. In this paper we present a new approach for contextual pre-filtering (i.e. using the current context to select a relevant subset of data). Our approach can be used with existing recommendation algorithms. It is based on two ontologies: Recommender System Context ontology, which represents the context, and Contextual Ontological User Profile ontology, which represents user preferences. We evaluated our approach through an offline study which showed that when used with well-known recommendation algorithms it can significantly improve the accuracy of prediction.

关键词： Context Ontologies Context modeling Vocabulary Recommender systems Motion pictures Prediction algorithms

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Towards interoperable, cognitive and autonomic IoT systems: An agent-based approach

Towards interoperable, cognitive and autonomic IoT systems: ...

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IEEE World Forum on Internet of Things (WF-IoT)

作者： Claudio Savaglio Giancarlo Fortino Mengchu Zhou Dept. of Informatics Modeling Electronics and Systems University of Calabria Rende CS Italy Dept. of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA

ISBN: (纸本)9781509041312

Within the Information and Communication technology hype cycle the Internet of Things (IoT) represents a prominent subject, being rich in potentiality as well as in development issues. In this paper, we face the IoT developing process first “in the small” by designing the Smart Objects (SOs, representing the fundamental IoT building blocks) as agents, and after “in the large” by treating the IoT systems as Multi Agent Systems (MASs). Indeed, the agent abstraction is a suitable paradigm to instill smartness and autonomy within a single SO and consequently to realize distributed, self-steering and heterogeneous IoT systems. In such directions, the Agent-based COoperating SO (ACOSO) middleware represents a viable solution for the programming, development and management of agent-based SO systems while its performance verification on different IoT networks of different scale has been made through the Omnet++ simulator.

关键词： Interoperability Internet of Things Agent-based computing Cognitive Systems Autonomic Computing

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