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IEEE Sensors

作者： Cesar A. da Silva Marcelo A. C. Ismael Claudio M. Zaina Linnyer B. Ruiz Graduate Program in Electrical Engineering Federal University of Minas Gerais Belo Horizonte MG Brazil Department of Computing Federal Institute of São Paulo Presidente Epitácio SP Brazil Graduate Program in Computer Science State University of Maringá Maringá PR Brazil

The task of designing WMSN real scenarios in order to evaluate the network performance is not trivial. This work sheds some light on this challenge by studying the impact of the load size when using ZigBee protocol in WMSN that transmits images. The main feature is to use real nodes for reading and dividing camera data into packages for transmission over the network. We have analyzed the number of packets transmitted by sensor node and the number of packets received by base station as a success parameter of the delivery. We have also analyzed data delay and data delivery for each load size: 64, 80 and 96 bytes. The results reveal that there is a trade-off between latency and success rate and that the packet size definition can promote the productivity of network resources and the quality of the provided services.

关键词： Protocols ZigBee Wireless sensor networks Cameras Base stations Image communication IEEE 802.15 Standard

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TODIM Based Method to Process Heterogeneous Information

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Procedia computer science 2015年 55卷 318-327页

作者： Rodolfo Lourenzutti Renato A. Krohling Graduate Program in Computer Science PPGI UFES Federal University of Espirito Santo Av. Fernando Ferrari 514 Vitoria CEP 29075-910 Brazil Department of Production Engineering & Graduate Program in Computer Science PPGI UFES - Federal University of Espirito Santo Av. Fernando Ferrari 514 Vitoria CEP 29075-910 Esprito Santo ES Brazil

Multicriteria decision making (MCDM) problems are getting increasingly difficult over the years. Nowadays, it is very common to have a problem where heterogeneous types of information must be processed before making a decision. From a wide variety of MCDM methods, just a few of them are able to process mixed types of information at the same time and most of these methods relies on transformations that may cause problems and/or be unjustified. In this paper we bring a modular interpretation of the TODIM (an acronym in Portuguese for Interative Multi-criteria Decision Making) method to handle heterogeneous data types simultaneously, in a systematic way. We argue that the method have a modular capacity which is the novelty of our approach. Using this interpretation, the whole problem with heterogeneous information is broken into modules and processed in a straightforward way. Two examples are used to illustrate the approach showing the effectiveness and practicability.

关键词： Multi-criteria decision making (MCDM) TODIM heterogeneous information interval numbers fuzzy numbers intuitionistic fuzzy numbers.

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Matched computed tomography segmentation and demographic data for oropharyngeal cancer radiomics challenges

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Scientific data 2017年第1期4卷 170077-170077页

作者： Hesham Elhalawani Abdallah S.R. Mohamed Aubrey L. White James Zafereo Andrew J. Wong Joel E. Berends Shady AboHashem Bowman Williams Jeremy M. Aymard Aasheesh Kanwar Subha Perni Crosby D. Rock Luke Cooksey Shauna Campbell Yao Ding Clifton D. Fuller Stephen Y. Lai Elisabeta G. Marai David Vock Guadalupe M. Canahuate John Freymann Keyvan Farahani Jayashree Kalpathy-Cramer Department of Radiation Oncology University of Texas MD Anderson Cancer Center Houston 77030 Texas USA Department of Clinical Oncology University of Alexandria Alexandria 21527 Egypt McGovern Medical School at University of Texas Health Science Center at Houston (UTHealth) Houston 77030 Texas USA University of Texas Health Science Center San Antonio 78229 Texas USA Department of Cardiology Harvard Medical School and Massachusetts General Hospital Boston 02115 Massachusetts USA Furman University Greenville 29613 South Carolina USA Abilene Christian University Abilene 79601 Texas USA Texas Tech University Health Sciences Center School of Medicine Lubbock 79905 Texas USA Columbia College of Physicians and Surgeons New York 10032 Massachusetts USA Texas Tech Health Sciences Center El Paso Paul L. Foster School of Medicine 79905 Texas USA Department of Radiation Oncology Cleveland Clinic Foundation Cleveland 44124 Ohio USA Department of Imaging Physic University of Texas MD Anderson Cancer Center Houston 77030 Texas USA Medical Physics Program University of Texas Graduate School of Biomedical Sciences Houston 77030 Texas USA Department of Head and Neck Surgery University of Texas MD Anderson Cancer Center Houston 77030 Texas USA Department of Computer Science University of Illinois at Chicago Chicago 60607 Illinois USA Department of Biostatistics University of Minnesota of Public Health Minneapolis 55455 Minnesota USA Department of Electrical & Computer Engineering University of Iowa Iowa City 52242 Iowa USA Leidos Biomedical Research Inc Frederick National Laboratory for Cancer Research Frederick 21701 Maryland USA The Russell H. Morgan Department of Radiology and Radiological Science Johns Hopkins Medical Institutions Baltimore 21287 Maryland USA National Cancer Institute National Institutes of Health Bethesda 20892 Maryland USA Department of Radiology and Athinoula A. Martinos Center for Biomedical Imaging Massachusetts Ge

Cancers arising from the oropharynx have become increasingly more studied in the past few years, as they are now epidemic domestically. These tumors are treated with definitive (chemo)radiotherapy, and have local recurrence as a primary mode of clinical failure. Recent data suggest that 'radiomics', or extraction of image texture analysis to generate mineable quantitative data from medical images, can reflect phenotypes for various cancers. Several groups have shown that developed radiomic signatures, in head and neck cancers, can be correlated with survival outcomes. This data descriptor defines a repository for head and neck radiomic challenges, executed via a Kaggle in Class platform, in partnership with the MICCAI society 2016 annual *** public challenges were designed to leverage radiomics and/or machine learning workflows to discriminate HPV phenotype in one challenge (HPV status challenge) and to identify patients who will develop a local recurrence in the primary tumor volume in the second one (Local recurrence prediction challenge) in a segmented, clinically curated anonymized oropharyngeal cancer (OPC) data set.

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A Hyper-Heuristic for the Environmental/Economic Dispatch Optimization Problem

A Hyper-Heuristic for the Environmental/Economic Dispatch Op...

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Brazilian Conference on Intelligent Systems (BRACIS)

作者： Richard A. Gonçalves Carolina P. Almeida Sandra M. Venske Josiel N. Kuk Lucas M. Pavelski Myriam R. Delgado Computer Science Department UNICENTRO Guarapuava PR Brazil Graduate Program in Electrical and Computer Engineering Federal University of Paraná Curitiba PR Brazil

Hyper-Heuristics are high-level methodologies developed to select or generate heuristics for solving complex problems. Despite their success, there is a lack of multi-objective hyper-heuristics. In the multi-objective optimization context, MOEA/D decomposes a problem into a number of sub problems handled by individuals in a collaborative manner. Our approach, named MOEA/D-HH SW , expands the MOEA/D framework with a multi-objective selection hyper-heuristic. It uses the proposed adaptive choice function with sliding window to determine which low-level heuristic (differential evolution operators) should be applied by each individual during MOEA/D execution. The proposed approach is tested in three known instances of the multi-objective environmental/economic dispatch problem, formulated as a non-linear constrained optimization problem with competing and non-commensurable objectives. MOEA/D-HH SW outperforms state-of-the-art algorithms reported in the literature for all considered instances.

关键词： Optimization Fuels Generators Sociology Statistics Propagation losses Mathematical model

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Search for heavy resonances decaying to a Z boson and a photon in pp collisions at s=13 TeV with the ATLAS detector

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Physics Letters, Section B: Nuclear, Elementary Particle and High-Energy Physics 2017年 764卷 11-30页

作者： Aaboud, M. Aad, G. Abbott, B. Abdallah, J. Abdinov, O. Abeloos, B. Aben, R. AbouZeid, O.S. Abraham, N.L. Abramowicz, H. Abreu, H. Abreu, R. Abulaiti, Y. Acharya, B.S. Adachi, S. Adamczyk, L. Adams, D.L. Adelman, J. Adomeit, S. Adye, T. Affolder, A.A. Agatonovic-Jovin, T. Agricola, J. Aguilar-Saavedra, J.A. Ahlen, S.P. Ahmadov, F. Aielli, G. Akerstedt, H. Åkesson, T.P.A. Akimov, A.V. Alberghi, G.L. Albert, J. Albrand, S. Alconada Verzini, M.J. Aleksa, M. Aleksandrov, I.N. Alexa, C. Alexander, G. Alexopoulos, T. Alhroob, M. Ali, B. Aliev, M. Alimonti, G. Alison, J. Alkire, S.P. Allbrooke, B.M.M. Allen, B.W. Allport, P.P. Aloisio, A. Alonso, A. Alonso, F. Alpigiani, C. Alshehri, A.A. Alstaty, M. Alvarez Gonzalez, B. Álvarez Piqueras, D. Alviggi, M.G. Amadio, B.T. Amako, K. Amaral Coutinho, Y. Amelung, C. Amidei, D. Amor Dos Santos, S.P. Amorim, A. Amoroso, S. Amundsen, G. Anastopoulos, C. Ancu, L.S. Andari, N. Andeen, T. Anders, C.F. Anders, G. Anders, J.K. Anderson, K.J. Andreazza, A. Andrei, V. Angelidakis, S. Angelozzi, I. Anger, P. Angerami, A. Anghinolfi, F. Anisenkov, A.V. Anjos, N. Annovi, A. Antel, C. Antonelli, M. Antonov, A. Anulli, F. Aoki, M. Aperio Bella, L. Arabidze, G. Arai, Y. Araque, J.P. Arce, A.T.H. Arduh, F.A. Arguin, J-F. Argyropoulos, S. Arik, M. Armbruster, A.J. Armitage, L.J. Arnaez, O. Arnold, H. Arratia, M. Arslan, O. Artamonov, A. Artoni, G. Artz, S. Asai, S. Asbah, N. Ashkenazi, A. Åsman, B. Asquith, L. Assamagan, K. Astalos, R. Atkinson, M. Atlay, N.B. Augsten, K. Avolio, G. Axen, B. Ayoub, M.K. Azuelos, G. Baak, M.A. Baas, A.E. Baca, M.J. Bachacou, H. Bachas, K. Backes, M. Backhaus, M. Bagiacchi, P. Bagnaia, P. Bai, Y. Baines, J.T. Baker, O.K. Baldin, E.M. Balek, P. Balestri, T. Balli, F. Balunas, W.K. Banas, E. Banerjee, Sw. Bannoura, A.A.E. Barak, L. Barberio, E.L. Barberis, D. Barbero, M. Barillari, T. Barisits, M-S Barklow, T. Barlow, N. Barnes, S.L. Barnett, B.M. Barnett, R.M. Barnovska-Blenessy, Z. Baroncelli, A. Barone, G. Barr, A.J. Barranco Navarro, L. Barreiro, F. Barreiro Gui Department of Physics University of Adelaide Adelaide Australia Physics Department SUNY Albany Albany NY United States Department of Physics University of Alberta Edmonton AB Canada Department of Physics Ankara University Ankara Turkey Istanbul Aydin University Istanbul Turkey Division of Physics TOBB University of Economics and Technology Ankara Turkey LAPP CNRS/IN2P3 Université Savoie Mont Blanc Annecy-le-Vieux France High Energy Physics Division Argonne National Laboratory Argonne IL United States Department of Physics University of Arizona Tucson AZ United States Department of Physics The University of Texas at Arlington Arlington TX United States Physics Department University of Athens Athens Greece Physics Department National Technical University of Athens Zografou Greece Department of Physics The University of Texas at Austin Austin TX United States Institute of Physics Azerbaijan Academy of Sciences Baku Azerbaijan Institut de Física d'Altes Energies (IFAE) The Barcelona Institute of Science and Technology Barcelona Spain Institute of Physics University of Belgrade Belgrade Serbia Department for Physics and Technology University of Bergen Bergen Norway Physics Division Lawrence Berkeley National Laboratory University of California Berkeley CA United States Department of Physics Humboldt University Berlin Germany Albert Einstein Center for Fundamental Physics Laboratory for High Energy Physics University of Bern Bern Switzerland School of Physics and Astronomy University of Birmingham Birmingham United Kingdom Department of Physics Bogazici University Istanbul Turkey Department of Physics Engineering Gaziantep University Gaziantep Turkey Istanbul Bilgi University Faculty of Engineering and Natural Sciences Istanbul Turkey Bahcesehir University Faculty of Engineering and Natural Sciences Istanbul Turkey Centro de Investigaciones Universidad Antonio Narino Bogota Colombia INFN Sezione di Bologna Italy Dipartimento di Fis

This Letter presents a search for new resonances with mass larger than 250 GeV, decaying to a Z boson and a photon. The dataset consists of an integrated luminosity of 3.2 fb−1 of pp collisions collected at s=13 TeV w... 详细信息

This Letter presents a search for new resonances with mass larger than 250 GeV, decaying to a Z boson and a photon. The dataset consists of an integrated luminosity of 3.2 fb⁻¹ of pp collisions collected at s=13 TeV with the ATLAS detector at the Large Hadron Collider. The Z bosons are identified through their decays either to charged, light, lepton pairs (e⁺e⁻, μ⁺μ⁻) or to hadrons. The data are found to be consistent with the expected background in the whole mass range investigated and upper limits are set on the production cross section times decay branching ratio to Zγ of a narrow scalar boson with mass between 250 GeV and 2.75 TeV. © 2016 The Author(s)

关键词： Z bosons CROSS sections (Nuclear physics) PHOTON-photon interactions LARGE Hadron Collider (France & Switzerland) DILEPTON production NUCLEAR counters

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Intrinsic Raman signatures of pristine hybrid perovskite CH3NH3PbI3 and its multiple stages of structure transformation

Intrinsic Raman signatures of pristine hybrid perovskite CH3...

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2016 IEEE 43rd Photovoltaic Specialists Conference (PVSC)

作者： Qiong Chen Henan Liu Hui-Seon Kim Yucheng Liu Mengjin Yang Naili Yue Gang Ren Kai Zhu Shengzhong Frank Liu Nam-Gyu Park Yong Zhang Department of Electrical and Computer Engineering The University of North Carolina at Charlotte Charlotte NC USA Optical Science and Engineering graduate program The University of North Carolina at Charlotte Charlotte NC USA Department of Energy Science Sungkyunkwan University Suwon South Korea National Ministry of Education Shaanxi Normal University Xi'an China Chemical and Materials Science Center National Renewable Energy Laboratory CO USA Molecular Foundry Lawrence Berkeley National Laboratory Berkeley CA USA Key Laboratory of Applied Surface and Colloid Chemistry National Ministry of Education Shaanxi Normal University Xi'an Shaanxi CN School of Chemical Engineering Sungkyunkwan University Suwon South Korea University of North Carolina at Charlotte Charlotte NC US

By performing spatially resolved Raman and photoluminescence spectroscopy with different illumination conditions, we have achieved a unified understanding towards the spectroscopy signatures of the organic-inorganic hybrid perovskite, transforming from the pristine state (CH 3 NH 3 PbI 3 or MAPbI 3 ) to fully degraded state (i.e., PbI 2 ), for samples with varying crystalline domain size from mesoscopic scale to macroscopic size, synthesized by three different techniques.

关键词： Measurement by laser beam Density measurement Chemistry Lighting Optical films Degradation Spectroscopy

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A Kinect-Aided Method to Estimate the Fundus Camera Extrinsic Parameters for Three-Dimensional Reconstruction of Retinal Blood Vessels

A Kinect-Aided Method to Estimate the Fundus Camera Extrinsi...

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Future Technologies Conference

作者： E. Hernandez-Sanchez M. Elena Martinez-Perez A. Gastelum-Strozzi Engineering Graduate Program Universidad Nacional Autónoma de México. Ciudad de México Computer Science Department IIMAS Universidad Nacional Autónoma de México. Apartado Postal 20-126 Ciudad de México C.P. 01000 CCADET-HGM. Universidad Nacional Autónoma de México. Ciudad de México

ISBN: (纸本)9781509041725

This paper deals with the estimation of intrinsic and extrinsic parameters in a fundus camera system. These parameters are fundamental to retrieve three-dimensional reconstruction of eye's structure, in our case, retinal blood vessels. In this paper we used the Zhang's algorithm to estimate the intrinsic parameters of the optical system. Besides, an alternative method to estimate the extrinsic parameters is proposed based on the kinect one sensor. These modifications provide an easy way to characterise the whole fundus camera system. Experimental validation was carried out to verify the accuracy of the proposed method. A cylindrical known object was reconstructed having and average error of 3.96%. A real eye's structure was also reconstructed from a fundus image pair.

关键词： Fundus images 3D reconstruction Camera calibration Retinal blood vessels

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Dimensioning Microwave Wireless Networks

Dimensioning Microwave Wireless Networks

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IEEE International Conference on Communications

作者： Alvinice Kodjo Brigitte Jaumard Napoleao Nepomuceno Mejdi Kaddour David Coudert Inria France & Univ. Nice Sophia Antipolis Department of Computer Science and Software Engineering Concordia University Montreal Graduate Program in Applied Informatics University of Fortaleza Department of Computer Science University of Oran

ISBN: (纸本)9781467364300

We aim at dimensioning fixed broadband microwave wireless networks under unreliable channel conditions. As the transport capacity of microwave links is prone to variations due to, e.g., weather conditions, such a dimensioning requires special attention. It can be formulated as the determination of the minimum cost bandwidth assignment of the links in the network for which traffic requirements can be met with high probability, while taking into account that transport link capacities vary depending on channel conditions. The proposed optimization model represents a major step forward since we consider dynamic routing. Experimental results show that the resulting solutions can save up to 45% of the bandwidth cost compared to the case where a bandwidth over-provisioning policy is uniformly applied to all links in the network planning. Comparisons with previous work also show that we can solve much larger instances in significantly shorter computing times, with a comparable level of reliability.

关键词： Bandwidth Modulation Pricing Reliability Microwave communication Routing

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Abstracts and Workshops 7th National Spinal Cord Injury Conference November 9-11, 2017 Fallsview Casino Resort Niagara Falls, Ontario, Canada Abstracts

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JOURNAL OF SPINAL CORD MEDICINE 2017年第6期40卷 813-869页

作者： [Anonymous] a NET Team Toronto Rehabilitation Institute - University Health Network Toronto ON Canada. fo Neural Engineering and Therapeutic Team Lyndhurst Centre Toronto Rehabilitation Institute - University Health Network Toronto ON Canada. c Rick Hansen Institute Vancouver BC Canada. ev Rick Hansen Institute Vancouver BC Canada. fc Stan Cassidy Hospital University of New Brunswick Fredericton NB Canada. fd Dalhousie University Halifax NS Canada. e University of Saskatchewan Saskatoon SK Canada. aa University of Calgary Calgary AB Canada. y Dalhousie University Halifax NS Canada. fa Health Sciences Centre Winnipeg MB Canada. fb University of Manitoba Winnipeg MB Canada. h University of Alberta Edmonton AB Canada. i Universite Laval Quebe c City QC Canada. bd Rick Hansen Institute Vancouver BC Canada. fz Clinician Investigator Lyndhurst Centre Toronto Rehabilitation Institute University Health Network and Assistant Professor Department of Medicine Division of Physical Medicine and Rehabilitation University of Toronto. v University of Toront o Toronto ON Canada. n Institute of Biomaterials and Biomedical Engineering University of Toronto Toronto ON Canada. o Toronto Rehabilitation Institute - University Health Network Toronto ON Canada. ga Clinical Scientist Lyndhurst Centre Toronto Rehabilitation Institute University Health Network and Assistant Professor Department of Physical Therapy University of Toronto. dx Department of Electrical and Computer Engineering University of Toronto Toronto ON Canada. fm Lawson Health Research Institute London ON Canada. r Parkwood Institute London ON Canada. bi Parkwood Institute London ON Canada. s University of British Columbia Vancouver BC Canada. t Simon Fraser University Burnaby BC Canada. u DeltaQuest Foundation Concord MA USA. z Institut national d'excellence en santé et en services sociaux (INESSS) Quebec City QC Ca

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Differential Evolution and Nelder-mead for Constrained Non-linear Integer Optimization Problems

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Procedia computer science 2015年 55卷 668-677页

作者： Felipe Luchi Renato A. Krohling Graduate Program in Science Computer PPGI UFES - Federal University of Esṕırito Santo Av. Fernando Ferrari 514 CEP 29075-910 Vitória Esṕırito Santo ES Brazil Departament of Production Engineering & Graduate Program in Computer Science PPGI UFES - Federal University of Esṕırito Santo Av. Fernando Ferrari 514 CEP 29075-910 Vitória Esṕırito Santo ES Brazil

We present a novel approach to solve constrained non-linear integer optimization problems based on Differential Evolution (DE) and Nelder-Mead (NM). DE is a promising technique used in non-differentiable and non-linear problems with continuous variables. It is used to identify promising regions in the search space. NM is a derivative-free technique used in non-linear continuous optimization problems. Since we are concerned with integer problems, then the NM is extended to handle with integer optimization problems. The constraints are treated by the Alpha Constrained method, where constraints values and fitness are compared using a lexicographical order. Since DE is used to continuous optimization and NM needs an initial starting point, we propose a method that use the best individual of DE as starting point to NM. Simulation results show the effectiveness of the proposed method.

关键词： Constrained non-linear integer optimization Differential Evolution Nelder-Mead Alpha Constraint method

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