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37th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2017

作者： De Souza, Marcelo K. Veronez, Mauricio R. Tognoli, Francisco M. W. Gonzaga, Luiz De Souza, Lais V. Kochhann, Marcus V. L. Da Silva, Nadine G. Marson, Fernando P. Cagliari, Joice Graduate Program in Geology Vale Do Rio Dos Sinos University São Leopoldo RS Brazil Vale Do Rio Dos Sinos University São Leopoldo RS Brazil Graduate Program in Applied Computing Vale Do Rio Dos Sinos University São Leopoldo RS Brazil

ISBN: (纸本)9781509049516

We investigate here the potential of the spectroscopy in the identification and quantification of mixtures of kaolinite and goethite from the Continuum Removal (CR) of the spectra in the short-wave infrared. For this purpose, spectral measurements of the kaolinite, goethite, and controlled mixtures of these minerals were systematically performed. The continuum of the results were removed, the depth of the kaolinite diagnostic absorption was calculated and compared with a spectral library. It was possible to identify the kaolinite with high determination coefficient (R2>0.95) when its proportion reaches at least 60% in the mixture. For quantification purposes, it was possible to quantify kaolinite using the diagnostic absorption feature depth in the CR with a coefficient of determination of 0.99. © 2017 IEEE.

关键词： Absorption Minerals Reflectivity Spectroscopy Libraries Geologic measurements Remote sensing

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Escada: Predicting Virtual Machine Network Bandwidth Demands for Elastic Provisioning in IaaS Clouds 4

Escada: Predicting Virtual Machine Network Bandwidth Demands...

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4th IEEE International Conference on Cloud and Autonomic computing, ICCAC 2017

作者： Marques, Jonatas Adilson Obelheiro, Rafael Rodrigues Institute of Informatics Federal University of Rio Grande Do sul Porto Alegre Brazil Graduate Program in Applied Computing Department of Computer Science Santa Catarina State University Joinville Brazil

ISBN: (纸本)9781538619391

In Infrastructure as a Service clouds, customers lease virtual resources (e.g., CPU, memory, network) offered by cloud providers, paying for the allocated capacity of resources, regardless of their effective use. In this context, it is in the interest of the customers to reserve resources with sufficient capacity so that their applications achieve good performance while, at the same time, minimizing their expenses with idle capacities. The correct provisioning of resources is also invaluable to providers, who seek to maximize the resource usage of their physical infrastructures, avoiding spending maintenance costs with unused hardware such as high capacity servers and networking devices. We introduce Escada, a novel model for network bandwidth prediction to guide the provisioning of virtual machines. Escada is application-oblivious and dynamically adapts to changes in a virtual machine workload profile. The network flows of a virtual machine are monitored and used to estimate its total required bandwidth over a time period. A prediction algorithm is then applied to the entire history of estimates to predict the virtual machine future required bandwidth. Our experimental evaluation shows that the estimates provided by Escada are useful for guiding the prediction of network bandwidth requirements, providing accurate bandwidth estimates even when the network is under-provisioned. Furthermore, Escada correctly adjusts its prediction algorithm faster than the state-of-the-art model and predicts more reliably during the adjusting period. © 2017 IEEE.

关键词： Virtual machine

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Playing the Original Game Boy Tetris Using a Real Coded Genetic Algorithm

Playing the Original Game Boy Tetris Using a Real Coded Gene...

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Brazilian Conference on Intelligent Systems (BRACIS)

作者： Renan Samuel da Silva Rafael Stubs Parpinelli Graduate Program in Applied Computing State University of Santa Catarina Joinville Brazil

Tetris is a very popular game, having sold more than 450 millions units according to Forbes and it is also a very popular research subject in the field of Artificial Intelligence and Computational Intelligence. This work has two main goals. The first goal consists of providing a standardized testing scenario based on an Emulator to run the Original Tetris Game. The second goal is to test several feature sets found in the literature in the proposed Real Coded Genetic Algorithm Based Agent. The results obtained showed the viability of having an agent playing the Original Tetris Game.

关键词： Games Genetic algorithms Standards Artificial neural networks Testing Emulation Sociology

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The Protein Structure Prediction Problem Approached by a Cascade Differential Evolution Algorithm Using ROSETTA

The Protein Structure Prediction Problem Approached by a Cas...

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Brazilian Conference on Intelligent Systems (BRACIS)

作者： Pedro Henrique Narloch Rafael Stubs Parpinelli Graduate Program in Applied Computing State University of Santa Catarina Joinville Brazil

The Protein Structure Prediction (PSP) is one of the most challenging problems in Bioinformatics. In computationally terms, the PSP is classified as a NP-complete problem. In this way, metaheuristics became very interesting to find good solutions in a plausible processing time. In this work we propose a distinct Differential Evolution approach that mix different mutation mechanisms (DEcascade) to solve the PSP using the backbone side chain torsion angles representation with the ROSETTA energy function. Four proteins are used in the experiments: 1ZDD, 1CRN, 1ENH and 1AIL. To evaluate the proposed approach, two variations of DEcascade are used and compared with singlemutation mechanisms DE and literature work. Both variations showed competitive results when compared with the literature and better energy values than other DE approaches. Also, the population diversity is monitored during the optimization process showing that the diversity balance is a key feature for good solutions.

关键词： Proteins Sociology Statistics Optimization Prediction algorithms Lattices Amino acids

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Gamification strategies for mobile device applications: A systematic review

Gamification strategies for mobile device applications: A sy...

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Iberian Conference on Information Systems and Technologies (CISTI)

作者： Nathália Pinto Cechetti Daiana Biduki Ana Carolina Bertoletti De Marchi Graduate Program in Applied Computing Universidade de Passo Fundo - UPF Brazil

ISBN: (纸本)9781509050475

In the quest to engage and motivate users on the use of mobile applications, the gamification concept has been excelling in the market since incorporates game elements in a non-game context. Scoring systems, challenges, competitions and badges, are some of the elements implemented in many fields, such as health, education, ecological awareness, among others. In this context, this study aimed to systematically review available literature to identify gamification strategies used in mobile applications. A search was conducted in ACM, Science Direct and Scopus databases, from March to June 2016. A total of 402 studies were found, 23 of which met the eligibility criteria. The results demonstrated the heterogeneity of gamification elements being used and the impact they caused in the applications, especially as a motivational factor for users. This study provides the basis for future research on gamification methods and emphasizes the importance of this concept to increase engagement and provide enjoyment to users.

关键词： Mobile communication Games Education Databases Mobile applications Crowdsourcing Systematics

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Scheduling services for MANETs using genetic algorithms

Scheduling services for MANETs using genetic algorithms

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Marcelo Petri Janine Kniess Rafael Stubs Parpinelli Graduate Program in Applied Computing Santa Catarina State University Joinville Brasil

This paper presents a genetic algorithm for resource scheduling in service discovery to MANETs operating in emergency scenarios. The shared resources could be ambulances or support cars. Through an appropriate model for scheduling resources, we aim to attend the greatest number of victims in the affected area. Performance evaluation results on the Network Simulator NS-3 confirm the effectiveness of genetic algorithm for resource scheduling when compared to the A-Star algorithm which is simple heuristic method, that prioritizing paths that seem to be leading closer to the goal.

关键词： Protocols Genetic algorithms Scheduling Ad hoc networks Mobile computing Biological cells Processor scheduling

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Combined multiple neural networks and genetic algorithm with missing data treatment: Case study of water level forecasting in Dungun River - Malaysia

IAENG International Journal of Computer Science

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IAENG International Journal of Computer Science 2018年第2期45卷 246-254页

作者： Wibowo, Antoni Arbain, Siti Hajar Abidin, Norhaslinda Zainal Computer Science Department Binus Graduate Program-Master of Computer Science Bina Nusantara University Indonesia Faculty Computer Science Universiti Tun Hussein Onn Malaysia Malaysia Faculty of Computing Universiti Teknologi Malaysia Malaysia Department of Decision Sciences School of Quantitative Science Universiti Utara Malaysia Malaysia

We consider water level forecasting in Dungun River where the collected data contain missing values. Therefore, we cannot utilize a prediction technique to forecast the water level directly. To overcome this difficulty, we used Ordinary Linear Regression (OLR) and mean substitution to handle the imperfect data and to make the data meaningful. ARIMA and SARIMA are well known techniques and widely used in time series forecasting. Unfortunately, they produce a linear regression model that may improper model for water level forecasting. Instead, Backpropagation Neural Network (BPNN) and Nonlinear Autoregressive Exogenous Model (NARX) are alternative techniques to address the issue of linearity in regression. Nevertheless, they also have difficulties to determine the optimal network and regression coefficients/weights due to the randomness of their initial weights. Under this circumstance, we proposed Multiple BPNN and Genetic Algorithm (GA) to overcome the limitation of ARIMA/SARIMA, standalone BPNN and NARX. Our experiment showed that our proposed technique is superior compared to ARIMA, SARIMA, BPNN and NARX. © International Association of Engineers.

关键词： Neural networks

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Very-high-energy gamma-ray emission from GRB 201216C detected by MAGIC 37

Very-high-energy gamma-ray emission from GRB 201216C detecte...

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37th International Cosmic Ray Conference, ICRC 2021

作者： Fukami, Satoshi Berti, Alessio Loporchio, Serena Suda, Yusuke Nava, Lara Noda, Koji Bošnjak, Željka Asano, Katsuaki Longo, Francesco Acciari, V.A. Ansoldi, S. Antonelli, L.A. Arbet Engels, A. Artero, M. Baack, D. Babić, A. Baquero, A. Barres de Almeida, U. Barrio, J.A. Batković, I. Becerra González, J. Bednarek, W. Bellizzi, L. Bernardini, E. Bernardos, M. Besenrieder, J. Bhattacharyya, W. Bigongiari, C. Biland, A. Blanch, O. Bökenkamp, H. Bonnoli, G. Busetto, G. Carosi, R. Ceribella, G. Cerruti, M. Chai, Y. Chilingarian, A. Cikota, S. Colak, S.M. Colombo, E. Contreras, J.L. Cortina, J. Covino, S. D'Amico, G. D'Elia, V. Da Vela, P. Dazzi, F. De Angelis, A. De Lotto, B. Delfino, M. Delgado, J. Delgado Mendez, C. Depaoli, D. Di Pierro, F. Di Venere, L. Do Souto Espiñeira, E. Dominis Prester, D. Donini, A. Dorner, D. Doro, M. Elsaesser, D. Fallah Ramazani, V. Fattorini, A. Fonseca, M.V. Font, L. Fruck, C. Fukazawa, Y. García López, R.J. Garczarczyk, M. Gasparyan, S. Gaug, M. Giglietto, N. Giordano, F. Gliwny, P. Godinović, N. Green, J.G. Green, D. Hadasch, D. Hahn, A. Heckmann, L. Herrera, J. Hoang, J. Hrupec, D. Hütten, M. Inada, T. Ishio, K. Iwamura, Y. Jiménez Martínez, I. Jormanainen, J. Jouvin, L. Karjalainen, M. Kerszberg, D. Kobayashi, Y. Kubo, H. Kushida, J. Lamastra, A. Lelas, D. Leone, F. Lindfors, E. Linhoff, L. Lombardi, S. López-Coto, R. López-Moya, M. López-Oramas, A. Machado de Oliveira Fraga, B. Maggio, C. Majumdar, P. Makariev, M. Mallamaci, M. Maneva, G. Manganaro, M. Mannheim, K. Maraschi, L. Mariotti, M. Martínez, M. Mazin, D. Menchiari, S. Mender, S. Mićanović, S. Miceli, D. Miener, T. Miranda, J.M. Mirzoyan, R. Molina, E. Moralejo, A. Morcuende, D. Moreno, V. Moretti, E. Nakamori, T. Neustroev, V. Nigro, C. Nilsson, K. Nishijima, K. Nozaki, S. Ohtani, Y. Oka, T. Otero-Santos, J. Paiano, S. Palatiello, M. Paneque, D. Paoletti, R. Paredes, J.M. Pavletić, L. Peñil, P. Persic, M. Pihet, M. Prada Moroni, P.G. Prandini, E. Institute for Cosmic Ray Research The University of Tokyo Kashiwanoha 5-1-5 Kashiwa Japan Max Planck Institut for Physics Föhringer Ring 6 Munich Germany INFN MAGIC Group INFN Sezione di Bari Dipartimento Interateneo di Fisica Università e del Politecnico di Bari BariI-70125 Italy Physics Program Graduate School of Advanced Science and Engineering Hiroshima University Hiroshima739-8526 Japan Street number Merate Italy Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia University of Trieste Department of Physics via Valerio 2 Trieste Italy INFN Sezione di Trieste via Valerio 2 Trieste Italy Instituto de Astrofísica de Canarias Dpto. de Astrofísica Universidad de La Laguna Tenerife La LagunaE-38200 Spain Università di Udine INFN Trieste UdineI-33100 Italy RomeI-00136 Italy ETH Zürich ZürichCH-8093 Switzerland Bellaterra BarcelonaE-08193 Spain The University of Tokyo Chiba Kashiwa277-8582 Japan Technische Universität Dortmund DortmundD-44221 Germany Zagreb10000 Croatia IPARCOS Institute EMFTEL Department Universidad Complutense de Madrid MadridE-28040 Spain URCA RJ Rio de Janeiro22290-180 Brazil Università di Padova INFN PadovaI-35131 Italy University of Lodz Faculty of Physics and Applied Informatics Department of Astrophysics Lodz90-236 Poland Università di Siena INFN Pisa SienaI-53100 Italy ZeuthenD-15738 Germany Max-Planck-Institut für Physik MünchenD-80805 Germany Instituto de Astrofísica de Andalucía-CSIC Glorieta de la Astronomía s/n Granada18008 Spain Università di Pisa INFN Pisa PisaI-56126 Italy Universitat de Barcelona ICCUB IEEC-UB BarcelonaE-08028 Spain Armenian MAGIC Group A. Alikhanyan National Science Laboratory Yerevan0036 Armenia Centro de Investigaciones Energéticas Medioambientales y Tecnológicas MadridE-28040 Spain INFN MAGIC Group INFN Sezione di Torino Università degli Studi di Torino TorinoI-10125 Italy Croatian MAGIC Group University o

Gamma-ray bursts (GRBs) are the most energetic phenomena in the Universe. Many aspects of GRB physics are still under debate, such as the origin of their gamma-ray emission above the GeV energy range. In 2019, MAGIC detected TeV gamma rays from the long GRB 190114C, whose emission can be well explained by synchrotron-self Compton emission by relativistic electrons. However, it is still unclear whether such a process is common in GRBs, given the reduced number of GRBs detected until now at the very high energies (VHE). GRB 201216C is a long GRB and is the second one detected by MAGIC in this energy range. After receiving the alert provided by Swift-BAT, MAGIC automatically slewed to the GRB position, starting observations 56 seconds after the GRB onset. In the offline analyses of the collected data, we confirmed the detection of gamma-ray emission with a significance above 5 sigma. Following measurements from optical facilities, the redshift of this GRB was estimated to be z = 1.1. This makes GRB 201216C the most distant object ever detected by ground-based gamma-ray telescopes. In this contribution we will show the analysis results of the MAGIC data, also in comparison with past detected GRBs in the same energy range. Finally, accounting for available multi-wavelength observations, we will comment on the possible origin of the VHE emission detected by MAGIC. © Copyright owned by the author(s) under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0)

关键词： Germanium compounds

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Objective Reduction on Many-Objective Traffic Lights Signaling Optimization

Objective Reduction on Many-Objective Traffic Lights Signali...

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IEEE Symposium on Computers and Communications

作者： Saulo Matos Jonatas Vieira Leonardo Nogueira Matos Andre Britto Post-Graduate Program on Computer Science Federal University of Sergipe Sergipe Brazil Department of Computing Federal University of Sergipe Sergipe Brazil

Traffic Lights Signaling Optimization consists in optimizing traffic-light cycle using optimization algorithms. In this context, a traffic simulator can represent different road intersections and traffic lights and can calculate traffic quality measures. A solution to this problem can be encoded in a vector representing the time of each traffic light on the simulator and the objective functions are the traffic quality metrics. Since there are several metrics this problem can be defined as a many-objective optimization problem. In spite of the existence of several objective functions, the majority of the related work selects a small set, often two. This paper proposes a many-objective optimization framework based on objective reduction to solve Traffic lights Signaling Optimization Problem. Here, twelve objective functions are used. To deal with the high number of metrics, objective reduction techniques are applied along a multi-objective evolutionary algorithm. An experimental set is conducted to analyze if it possible to reduce the number of objective functions on the Traffic lights Signaling Optimization Problem and if this reduction enhances the performance of the optimization algorithm.

关键词： Traffic Lights Signaling Optimization Services for Smart Cities Many-Objective Optimization

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Optimizing a Homomorphic Filter for Illumination Compensation In Face Recognition Using Population-Based Algorithms

Optimizing a Homomorphic Filter for Illumination Compensatio...

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Workshop of Computer Vision

作者： Guilherme Felippe Plichoski Chidambaram Chidambaram Rafael Stubs Parpinelli Graduate Program in Applied Computing State University of Santa Catarina Joinville Santa Catarina Brazil

ISBN: (纸本)9781538614525

Face recognition (FR) systems based on populationbased heuristics algorithms is common nowadays. Depends on the approach, there is a need for tuning parameters in preprocessing step using optimization algorithms. Regarding FR challenges, the illumination variation is one of the critical factors. The homomorphic filter (HF) is one of the methods that can compensate ination aiding to stabilize the face images obtained under different lighting conditions. However, the HF requires some optimal parameters which can be possibly determined through optimization process. Based on this context, in this paper, we attempt to investigate the application of two population-based algorithms, the Jaya and the Particle Swarm Optimization (PSO), in order to optimize the HF parameters in CMU-PIE and BIOINFO face databases. The high performance of both algorithms shows that they are suitable to compensate the illumination variation achieving 100% and 91.3% recognition rates on CMUPIE and BIO-INFO, respectively.

关键词： Lighting Optimization Mathematical model Hafnium Face Face recognition Particle swarm optimization

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