Flow-Based Network Management: A Report from the IRTF NMRG Workshop

This is the report on the Workshop on Flow-Based Network Management, held within the 37th IRTF NMRG meeting, during IETF 93, on 24th July 2015, in Prague, Czech Republic. Following the tradition of the IRTF NMRG, the workshop focused on technologies, developments, and challenges of using flow-level traffic measurements for network management.     

MMORPGS and cognitive performance: A study with 1280 Brazilian high school students

The present paper attempts to empirically study the cognitive impacts of Massive Multiplayer Online Role-Playing Games (MMORPGs) in uncontrolled contexts in light of the Cognitive Mediation Networks Theory, a new model of human intelligence that aims to explain cognition as the result of brain activity combined with the information-processing done by external structures such as tools, social groups and culture. A sample of 1280 students Brazilian high school students answered a form inquiring about socio-demographic information plus the use of computer games, and also was submitted to a short knowledge exam and a mini psychometric test. The findings indicated that, due to their underlying structure and sociocultural nature, MMORPGs are associated to a greater level of insertion into the Digital Age, higher levels of logical-numerical performance, and better scholastic ability. Finally, suggestions are made for future studies on the subject.     

3D Face Recognition Using Simulated Annealing and the Surface Interpenetration Measure

This paper presents a novel automatic framework to perform 3D face recognition. The proposed method uses a Simulated Annealing-based approach (SA) for range image registration with the Surface Interpenetration Measure (SIM), as similarity measure, in order to match two face images. The authentication score is obtained by combining the SIM values corresponding to the matching of four different face regions: circular and elliptical areas around the nose, forehead, and the entire face region. Then, a modified SA approach is proposed taking advantage of invariant face regions to better handle facial expressions. Comprehensive experiments were performed on the FRGC v2 database, the largest available database of 3D face images composed of 4,007 images with different facial expressions. The experiments simulated both verification and identification systems and the results compared to those reported by state-of-the-art works. By using all of the images in the database, a verification rate of 96.5 percent was achieved at a False Acceptance Rate (FAR) of 0.1 percent. In the identification scenario, a rank-one accuracy of 98.4 percent was achieved. To the best of our knowledge, this is the highest rank-one score ever achieved for the FRGC v2 database when compared to results published in the literature.     

NUMERICAL SIMULATION OF DRYING IN A CYCLONE

ABSTRACT

This work presents a complete improved mathematical model of drying in cyclone. The slip condition of the particles on the wall, the heat transfer wall-panicle and the shrinkage of the panicles during the drying process were considered. The mathematical model considers a two-dimensional turbulent gas-particle flow where the panicle phase is treated as a continuum. The momentum equations of both particle and gas phases were written in cylindrical coordinates. The discretized equations were solved by the SIMPLE algorithm. Considering the slip condition to the panicle phase and the shrinkage of the material during the drying process it was revealed a better fitness between numerical and experimental results than the previous model.     

Estimation of water diffusivity parameters on grape dynamic drying

A computer program was developed, aiming at estimating water diffusivity parameters in a dynamic drying process with grapes, assessing the predictability of corresponding non-isothermal drying curves. It numerically solves Fick’s second law for a sphere, by explicit finite differences, in a shrinking system, with anisotropic properties and changing boundary conditions.     

The Experience in Designing and Evaluating the High Performance Cluster Netuno

This paper presents the Netuno supercomputer, a large-scale cluster installed at Federal University of Rio de Janeiro in Brazil. A detailed performance evaluation of Netuno is presented, depicting its computational and I/O performance, as well as the results for two real-world applications. Since building a high- performance cluster for running a wide range of applications is a non-trivial task, some lessons learned from assembling and operating this cluster, such as the excellent performance of the OpenMPI library, and the relevance of employing an efficient parallel file system over the traditional NFS system, can be useful knowledge to support the design of new systems. Currently, Netuno is being heavily used to run large scale simulations in the areas of ocean modeling, meteorology, engineering, physics, and geophysics.     

Novel Esterification of Glycerol Catalysed by Tin Chloride (II): A Recyclable and Less Corrosive Process for Production of Bio-Additives

Abstract  

In this work, a novel process based on use of a SnCl₂·2H₂O catalyst which is less corrosive, inexpensive, and a water tolerant Lewis acid was employed for synthesis of fuel bio-additives from glycerol. High yields and selectivities were achieved for glycerol esterification with acetic acid under mild reaction conditions. The SnCl₂ catalyst showed to be as active as p-toluene sulfonic and sulfuric acid, catalysts commonly used in acid-catalysed esterification reactions. However, its use has significant advantages in comparison to these Br?nsted acid catalysts, including lower reactor corrosion and unnecessary neutralization at the end reaction. The SnCl₂ catalyst can also be recovered and reused without loss of catalytic activity. Additionally, effects of reaction temperature, HOAc:glycerol molar ratio and catalyst concentration on both selectivity and yield of glycerol acetates were also investigated. The lower corrosiveness, facilitated handling, as well as potential for reuse without activity loss after simple recycle protocols are positive aspects of SnCl₂ catalysts.     

A neural network-based preset generation tool for a steel tandem cold mill

This paper traces the development of a software tool, based on a combination of artificial neural networks (ANN) and a few process equations, aiming to serve as a backup operation instrument in the reference generation for real-time controllers of a steel tandem cold mill. By emulating the mathematical model responsible for generating presets under normal operational conditions, the system works as an option to maintain plant operation in the event of a failure in the processing unit that executes the mathematical model. The system, built from the production data collected over six years of plant operation, steered to the replacement of the former backup operation mode (based on a lookup table), which degraded both product quality and plant productivity. The study showed that ANN are appropriated tools for the intended purpose and that by this instrument it is possible to achieve nearly the totality of the presets needed by this kind of process. The text characterizes the problem, relates the investigated options to solve it, justifies the choice of the ANN approach, describes the methodology and system implementation and, finally, shows and discusses the attained results.