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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Kleber de Aguiar Felipe M. G. França Valmir C. Barbosa César A. D. Teixeira Systems Engineering and Computer Science Program Federal University of Rio de Janeiro Rio de Janeiro RJ Brazil Centre for Informatics and Systems (CISUC) University of Coimbra Coimbra Portugal

This work introduces a new methodology for the early detection of epileptic seizure based on the WiSARD weightless neural network model and a new approach in terms of preprocessing the electroencephalogram (EEG) data. WiSARD has, among other advantages, the capacity of perform the training phase in a very fast way. This speed in training is due to the fact that WiSARD's neurons work like Random Access Memories (RAM) addressed by input patterns. Promising results were obtained in the anticipation of seizure onsets in four representative patients from the European Database on Epilepsy (EPILEPSIAE). The proposed seizure early detection WNN architecture was explored by varying the detection anticipation (δ) in the 2 to 30 seconds interval, and by adopting 2 and 3 seconds as the width of the Sliding Observation Window (SOW) input. While in the most challenging patient (A) one obtained accuracies from 99.57% (δ=2s; SOW=3s) to 72.56% (δ=30s; SOW=2s), patient D seizures could be detected in the 99.77% (δ=2s; SOW=2s) to 99.93% (δ=30s; SOW=3s) accuracy interval.

关键词： Electroencephalography Accuracy Training Databases Biological neural networks Epilepsy Feature extraction

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A six-degree-of-freedom robotic system for lower extremity rehabilitation

A six-degree-of-freedom robotic system for lower extremity r...

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IEEE International Conference on Rehabilitation Robotics (ICORR)

作者： Aaron Yurkewich S. Farokh Atashzar Ahmed Ayad Rajni V. Patel Canadian Surgical Technologies and Advanced Robotics (CSTAR) London ON Canada Department of Electrical & Computer Engineering The University of Western Ontario Mcchatronic Systems Engineering Program The University of Western Ontario

ISBN: (纸本)9781479918096

This paper describes the design, control and implementation of a sensorized robotic platform for versatile rehabilitation of stroke patients living with lower extremity neuromuscular deficit. The proposed device is composed of a six-degree-of-freedom actuation mechanism with a large workspace for lower extremity rehabilitation regimens. With a small footprint, lightweight, and low-cost design and a wireless interface this device is portable and well-suited for at-home and in-clinic use. A custom six-degree-of-freedom force/torque sensor was developed to measure real-time patient forces, and an admittance controller was implemented to provide assistive motion therapy. The results obtained show the suitability of this device for human-robot interaction for the implementation of lower extremity rehabilitation therapy.

关键词： Robot sensing systems Force Robot kinematics Medical treatment Extremities Torque

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Wave algorithm for recruitment in swarm robotics

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2015年 9156卷 3-13页

作者： Silva, Luneque Nedjah, Nadia Systems Engineering and Computer Science Program Federal University of Rio de Janeiro Rio de Janeiro Brazil Department of Electronics Engineering and Telecommunications State University of Rio de Janeiro Rio de Janeiro Brazil

In the last decades, studies on swarm robotics have grown significantly, with different new aspects becoming of interest in research. Although the primary interest in swarm robotics should be the application, which is the task that robots should perform, other aspects are also studied. For instance, in a robotic swarm, it may be necessary to select the robots that would perform a given task, aiming at a division of labor among the members. A similar problem is that of robot recruitment, required when a specific robot needs assistance to execute some tasks and thus needs to recruit other robots of the swarm to do so. In this paper, a distributed algorithm, termed the wave algorithm, is exploited to perform the recruitment based mainly on robot message passing to neighboring robots. © Springer International Publishing Switzerland 2015.

关键词： Message passing

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Learning Cellular Objectives from Fluxes by Inverse Optimization

Learning Cellular Objectives from Fluxes by Inverse Optimiza...

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IEEE Annual Conference on Decision and Control

作者： Qi Zhao Arion Stettner Ed Reznik Daniel Segre Ioannis Ch. Paschalidis Dept. of Electrical and Computer Eng. and Division of Systems Engineering Boston University Department of Biomedical Engineering Boston University Bioinformatics Program Department of Biology and Department of Biomedical Engineering Boston University

ISBN: (纸本)9781479978878

Flux Balance Analysis (FBA) is a widely used approach for studying biochemical networks, and in particular the genome-scale metabolic network reconstructions. It formulates the problem of predicting a cell's chemical reaction fluxes as the linear optimization problem of maximizing a cellular objective (e.g., growth) subject to constraints capturing stoichiometry mass balances of the metabolic network and bounds that reflect the composition of the growth medium. In practice, however, reaction fluxes of the cells under specific growth conditions are available to be measured, but the primal FBA objective function is not necessarily known. Understanding its structure can elucidate the cellular metabolic control mechanisms and infer important information regarding an organism's evolution. To that end, we have developed an Inverse Flux Balance Analysis (InvFBA) method which is a novel inverse optimization-based framework for inferring metabolic objective functions. Within this framework, we present three different forms of objective functions: linear, quadratic, and non-parametric. We show that in all cases, the inverse problem is tractable and can be solved efficiently. We provide several numerical examples to show that the inference of the objective function is consistent with simulated flux data and actual measurements.

关键词： Linear programming Kernel Optimization Biochemistry Biomass Biomedical measurement

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BioTIME 2.0: Expanding and Improving a Database of Biodiversity Time Series

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Global Ecology and Biogeography 2025年第5期34卷

作者： Maria Dornelas Laura H. Antão Amanda E. Bates Viviana Brambilla Jonathan M. Chase Cher F. Y. Chow Ada Fontrodona-Eslava Anne E. Magurran Inês S. Martins Faye Moyes Alban Sagouis Samuel Adu-Acheampong Daniel Acquah-Lamptey Dušan Adam Penelope A. Ajani Aitor Albaina Pablo Almaraz Jeongseop An Roger Sigismund Anderson Madelaine Jean Robertson Anderson Alexsander Z. Antunes Ivan Arismendi Linda Armbrecht Pedro Aros-Mardones Sreejith Kalpuzha Ashtamoorthy Narayanan Ayyappan Gal Badihi Joseph J. Bailey Andrew H. Baird Mark Edward Baird Sreekumar Vadakkethil Balakrishnan José António L. Barão-Nóbrega Adi Barash Miguel Barbosa Jos Barlow Claus Bässler Matthieu Beaumont Natalie Beenaerts Tiago Octavio Begot Wallace Beiroz Ricardo Beldade David M. Bell Alecia Bellgrove Jonathan Belmaker Lisandro Benedetti-Cecchi Cassandra E. Benkwitt Pamela Medina-van Berkum Brandon T. Bestelmeyer Matthew G. Betts Maxwell Kelvin Billah Anne D. Bjorkman Magdalena Błażewicz Christopher P. Bloch Shane A. Blowes Antonio Bode Juliano A. Bogoni Thomas Bolger Timothy C. Bonebrake Erik Bonsdorff Roberta Bottarin Luke N. Brokensha Rob W. Brooker Andrew J. Brooks Helge Bruelheide Thiago Almeida Bueno Claire Laguionie Mariana Lopes Campagnoli James Cant Erica Pellegrini Caramaschi Alexandre Caron Tadhg Carroll Tancredi Caruso Juan Carvajal-Quintero Giuseppe Castaldelli Edward Castañeda-Moya Pedro V. Castilho Sonia Zanini Cechin Shahar Chaikin Uchangi Manjunatha Chandrashekara Tory J. Chase Chaolun Allen Chen Jorge José Cherem Sei-Woong Choi Erica M. Christensen Alexander V. Christianini Jackson Wing Four Chu Peter Coad Carl Van Colen Lise Comte Elisabeth J. Cooper J. Hans C. Cornelissen Eddy Cosson Unai Cotano Luc Crevecoeur Shannan Kyle Crow Graeme S. Cumming Vanessa S. Daga Gabriella Damasceno Gergana N. Daskalova Claire H. Davies Robert A. Davis Frank P. Day Sussy De-La-Zerda Amy Elizabeth Deacon Indradatta de Castro-Arrazola Steven Degraer Kharran Deonarinesingh Juan C. Diaz-Ricaurte Christopher R. Dickman Tara Dirilgen Ciaran John Dolan J. Emmet Centre for Biological Diversity School of Biology University of St Andrews Fife UK MARE—Centro de Ciências do Mar e do Ambiente Faculdade de Ciências Universidade de Lisboa Lisboa Portugal Research Centre for Ecological Change Organismal and Evolutionary Biology Research Programme Faculty of Biological and Environmental Sciences University of Helsinki Helsinki Finland Department of Biology University of Victoria Victoria British Columbia Canada German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig Leipzig Germany Department of Computer Science Martin Luther University Halle-Wittenberg Halle (Saale) Germany Leverhulme Centre for Anthropocene Biodiversity Department of Biology University of York York UK Department of Animal Biology and Conservation Science University of Ghana Accra Ghana Philipps Universität Marburg Marburg Germany Department of Forest Ecology Silva Tarouca Research Institute Brno Czech Republic School of Life Sciences University of Technology Sydney Sydney New South Wales Australia Zoology and Animal Cell Biology Department University of the Basque Country (UPV/EHU) Leioa Spain Grupo de Oceanografía de Ecosistemas Instituto de Ciencias Marinas de Andalucía CSIC Campus Universitario de Puerto Real Puerto Real Spain National Institute of Ecology Seocheon Republic of Korea African Regional Postgraduate Programme in Insect Science University of Ghana Accra Ghana Département de Biologie Université de Sherbrooke Sherbrooke Quebec Canada Núcleo de Conservação da Biodiversidade Instituto de Pesquisas Ambientais Secretaria de Meio Ambiente Infraestrutura e Logística do Estado de São Paulo São Paulo Brazil Department of Fisheries Wildlife and Conservation Sciences Oregon State University Corvallis Oregon USA Institute for Marine and Antarctic Studies Ecology & Biodiversity Centre University of Tasmania Hobart Tasmania Australia Graduate Program in Oceanography Department of Oceanography Faculty of Natural Scienc

Motivation Here, we make available a second version of the BioTIME database, which compiles records of abundance estimates for species in sample events of ecological assemblages through time. The updated version expands version 1.0 of the database by doubling the number of studies and includes substantial additional curation to the taxonomic accuracy of the records, as well as the metadata. Moreover, we now provide an R package (BioTIMEr) to facilitate use of the database. Main Types of Variables Included The database is composed of one main data table containing the abundance records and 11 metadata tables. The data are organised in a hierarchy of scales where 11,989,233 records are nested in 1,603,067 sample events, from 553,253 sampling locations, which are nested in 708 studies. A study is defined as a sampling methodology applied to an assemblage for a minimum of 2 years. Spatial Location and Grain Sampling locations in BioTIME are distributed across the planet, including marine, terrestrial and freshwater realms. Spatial grain size and extent vary across studies depending on sampling methodology. We recommend gridding of sampling locations into areas of consistent size. Time Period and Grain The earliest time series in BioTIME start in 1874, and the most recent records are from 2023. Temporal grain and duration vary across studies. We recommend doing sample-level rarefaction to ensure consistent sampling effort through time before calculating any diversity metric. Major Taxa and Level of Measurement The database includes any eukaryotic taxa, with a combined total of 56,400 taxa. Software Format csv and. SQL.

关键词： assemblage biodiversity community database ecoinformatics species taxa time

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Elephant Herding Optimization

Elephant Herding Optimization

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International Symposium on Computational and Business Intelligence (ISCBI)

作者： Gai-Ge Wang Suash Deb Leandro dos S. Coelho School of Computer Science and Technology Jiangsu Normal University Xuzhou China Dept. of Computer Science & Engineering Cambridge Institute of Technology Ranchi INDIA Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana Curitiba Brazil

In this paper, a new kind of swarm-based metaheuristic search method, called Elephant Herding Optimization (EHO), is proposed for solving optimization tasks. The EHO method is inspired by the herding behavior of elephant group. In nature, the elephants belonging to different clans live together under the leadership of a matriarch, and the male elephants will leave their family group when they grow up. These two behaviors can be modelled into two following operators: clan updating operator and separating operator. In EHO, the elephants in each clan are updated by its current position and matriarch through clan updating operator. It is followed by the implementation of the separating operator which can enhance the population diversity at the later search phase. To demonstrate its effectiveness, EHO is benchmarked by fifteen test cases comparing with BBO, DE and GA. The results show that EHO can find the better values on most benchmark problems than those three metaheuristic algorithms.

关键词： Optimization Benchmark testing Sociology Statistics Particle swarm optimization Electronic mail Search methods

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Dense sampling of bird diversity increases power of comparative genomics (vol 587, pg 252, 2020)

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NATURE 2021年第7856期592卷 E24-E24页

作者： Feng, Shaohong Stiller, Josefin Deng, Yuan Armstrong, Joel Fang, Qi Reeve, Andrew Hart Xie, Duo Chen, Guangji Guo, Chunxue Faircloth, Brant C. Petersen, Bent Wang, Zongji Zhou, Qi Diekhans, Mark Chen, Wanjun Andreu-Sanchez, Sergio Margaryan, Ashot Howard, Jason Travis Parent, Carole Pacheco, George Sinding, Mikkel-Holger S. Puetz, Lara Cavill, Emily Ribeiro, Angela M. Eckhart, Leopold Fjeldsa, Jon Hosner, Peter A. Brumfield, Robb T. Christidis, Les Bertelsen, Mads F. Sicheritz-Ponten, Thomas Tietze, Dieter Thomas Robertson, Bruce C. Song, Gang Borgia, Gerald Claramunt, Santiago Lovette, Irby J. Cowen, Saul J. Njoroge, Peter Dumbacher, John Philip Ryder, Oliver A. Fuchs, Jerome Bunce, Michael Burt, David W. Cracraft, Joel Meng, Guanliang Hackett, Shannon J. Ryan, Peter G. Jonsson, Knud Andreas Jamieson, Ian G. da Fonseca, Rute R. Braun, Edward L. Houde, Peter Mirarab, Siavash Suh, Alexander Hansson, Bengt Ponnikas, Suvi Sigeman, Hanna Stervander, Martin Frandsen, Paul B. van der Zwan, Henriette van der Sluis, Rencia Visser, Carina Balakrishnan, Christopher N. Clark, Andrew G. Fitzpatrick, John W. Bowman, Reed Chen, Nancy Cloutier, Alison Sackton, Timothy B. Edwards, Scott V. Foote, Dustin J. Shakya, Subir B. Sheldon, Frederick H. Vignal, Alain Soares, Andre E. R. Shapiro, Beth Gonzalez-Solis, Jacob Ferrer-Obiol, Joan Rozas, Julio Riutort, Marta Tigano, Anna Friesen, Vicki Dalen, Love Urrutia, Araxi O. Szekely, Tamas Liu, Yang Campana, Michael G. Corvelo, Andre Fleischer, Robert C. Rutherford, Kim M. Gemmell, Neil J. Dussex, Nicolas Mouritsen, Henrik Thiele, Nadine Delmore, Kira Liedvogel, Miriam Franke, Andre Hoeppner, Marc P. Krone, Oliver Fudickar, Adam M. Mila, Borja Ketterson, Ellen D. Fidler, Andrew Eric Friis, Guillermo Parody-Merino, Angela M. Battley, Phil F. Cox, Murray P. Lima, Nicholas Costa Barroso Prosdocimi, Francisco Parchman, Thomas Lee Schlinger, Barney A. Loiselle, Bette A. Blake, John G. Lim, Haw Chuan Day, Lainy B. Fuxjager, Matthew J. Baldwin, Maude W. Braun, Michael J. Wirthlin, Morgan Dikow, China National GeneBank BGI-Shenzhen Shenzhen China State Key Laboratory of Genetic Resources and Evolution Kunming Institute of Zoology Chinese Academy of Sciences Kunming China BGI-Shenzhen Shenzhen China Villum Centre for Biodiversity Genomics Section for Ecology and Evolution Department of Biology University of Copenhagen Copenhagen Denmark BGI Education Center University of Chinese Academy of Sciences Shenzhen China MOE Laboratory of Biosystems Homeostasis and Protection Life Sciences Institute Zhejiang University Hangzhou China Department of Neuroscience and Developmental Biology University of Vienna Vienna Austria Center for Excellence in Animal Evolution and Genetics Chinese Academy of Sciences Kunming China James D. Watson Institute of Genome Sciences Hangzhou China UC Santa Cruz Genomics Institute UC Santa Cruz Santa Cruz CA USA Natural History Museum of Denmark University of Copenhagen Copenhagen Denmark Center for Macroecology Evolution and Climate GLOBE Institute University of Copenhagen Copenhagen Denmark Department of Biological Sciences Louisiana State University Baton Rouge LA USA Museum of Natural Science Louisiana State University Baton Rouge LA USA Centre of Excellence for Omics-Driven Computational Biodiscovery (COMBio) Faculty of Applied Sciences AIMST University Kedah Malaysia Section for Evolutionary Genomics The GLOBE Institute Faculty of Health and Medical Sciences University of Copenhagen Copenhagen Denmark Institute of Molecular Biology National Academy of Sciences Yerevan Armenia University Museum Norwegian University of Science and Technology Trondheim Norway Center for Reproductive Medicine The 2nd Affiliated Hospital School of Medicine Zhejiang University Hangzhou China Novogene Durham NC USA Duke University Medical Center Durham NC USA The Rockefeller University New York NY USA Howard Hughes Medical Institute Chevy Chase MD USA Department of Dermatology Medical University of Vienna Vienna Austria

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Investigating the Link between User Stories and Documentation Debt on Software Projects

Investigating the Link between User Stories and Documentatio...

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International Conference on Information Technology: New Generations (ITNG)

作者： Henrique F. Soares Nicolli S.R. Alves Thiago S. Mendes Manoel Mendonça Rodrigo O. Spínola Graduate Program in Systems and Computer at Salvador University Salvador Brazil Fraunhofer Project Center for Software and System Engineering at UFBA Salvador Brazil Federal Institute of Bahia - IFBA Salvador Brazil

Technical debt is a metaphor that describes the effect of immature artefacts in software development. One of its types is documentation debt, which can be identified by locating missing, inadequate or incomplete artefacts in software projects. Nowadays, we can observe more organizations using agile methods to support their activities. In particular, the use of user stories reduces the focus on requirement specification tasks and, as a consequence, creates difficulties that need to be overcame by the development team. In order to investigate these difficulties and assess whether they create a favourable scenario for incurring documentation debt, this paper presents the results of a literature review and an exploratory study. The results from both studies allowed us to identify a list of causes that can lead the development team to incur documentation debt when working with agile requirements. This is an important step in order to manage the technical debt from a preventive perspective.

关键词： Software Documentation Bibliographies Protocols Libraries Software engineering Estimation

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Using HMM in strategic games 9

Using HMM in strategic games

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9th International Workshop on Developments in Computational Models, DCM 2013

作者： Benevides, Mario Lima, Isaque Nader, Rafael Rougemont, Pedro Systems and Computer Engineering Program and Computer Science Department Federal University of Rio de Janeiro Brazil

In this paper we describe an approach to resolve strategic games in which players can assume different types along the game. Our goal is to infer which type the opponent is adopting at each moment so that we can increase the player's odds. To achieve that we use Markov games combined with hidden Markov model. We discuss a hypothetical example of a tennis game whose solution can be applied to any game with similar characteristics. © M. Benevides, I. Lima, R. Nader & P. Rougemont This work is licensed under the Creative Commons Attribution License.

关键词： Tennis

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Optimizing radar waveforms using generalized alternating projections

Optimizing radar waveforms using generalized alternating pro...

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Texas Symposium on Wireless and Microwave Circuits and systems, (WMCS)

作者： Dylan Eustice Charles Baylis Casey Latham Robert J. Marks Lawrence Cohen Wireless and Microwave Circuits and Systems Program Department of Electrical and Computer Engineering Baylor University Waco TX USA Radar Division United States Naval Research Laboratory Washington DC USA

The radar ambiguity function, described as an autocorrelation of shifts in time and frequency, is useful for determining a waveform's accuracy at detecting targets in certain range-Doppler combinations. An algorithm is proposed which uses a generalized method of alternating projections to synthesize waveforms with desired ambiguity function properties. In practice, it is often desirable to minimize the magnitude of the ambiguity function at range-Doppler combinations where targets other than the detection are likely to cause interference. The algorithm alternates between projections in the time, frequency, and range-Doppler domains until an optimal solution which fits desired ambiguity function properties is found. This work provides a computationally intelligent methodology to dynamically optimize detection in radar applications and a foundation for future work in joint circuit optimization for spectral compliance.

关键词： Minimization Time-frequency analysis Doppler effect Shape Time-domain analysis Radar

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