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Open Stack and Cloud Stack: Open Source Solutions for Building Public and Private Clouds

Open Stack and Cloud Stack: Open Source Solutions for Buildi...

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international symposium on symbolic and numeric algorithms for scientific computing (SYNASC)

作者： Amine Barkat Alysson Diniz dos Santos thi thao Nguyen Ho Dipartimento di Elettronica Informazione e Bioingegneria Milano Italy Politecnico di Milano Milano Lombardia IT

Cloud computing is continuously growing as a prominent technology for enterprises. While several giant public cloud providers, such as Amazon, Microsoft, IBM, Google are competing to extend their market, there is still a large number of organizations asking higher level of privacy and control over cloud solutions. therefore, the need to have private cloud solutions is obvious. To overcome this need there are several on-going open source software frameworks for building public and private clouds. Among them, Open Stack and Cloud Stack are growing at fast pace and gaining more attention. An analysis on these software stacks is necessary in order to choose the most suitable solution that matches an enterprise's requirements. this paper main contribution is an in depth study and comparison of the cloud properties of these two open source frameworks, providing useful information on open source cloud solutions that are not available elsewhere.

关键词： Cloud computing Servers Computer architecture Databases Virtual machine monitors Standards

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Application of symbolic Regression in Polymer Processing

Application of Symbolic Regression in Polymer Processing

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international symposium on symbolic and numeric algorithms for scientific computing (SYNASC)

作者： Wolfgang Roland Michael Kommenda Gerald R. Berger-Weber Institute of Polymer Processing and Digital Transformation Johannes Kepler University Linz Linz Austria Josef Ressel Centre for Symbolic Regression University of Applied Sciences Upper Austria Hagenberg Austria

Modeling and simulation is essential in polymer processing for predicting process characteristics and designing processing machines. Traditional models are based on analytical approaches. Over the last decades numerical simulation techniques have grown significantly with the rising computational power. With the ongoing digitalization the available data increased significantly and data-based modeling techniques have become popular also for production systems. Utilizing the available data powerful models, for instance, decision trees and artificial neural networks, can be trained. the prediction accuracy is strongly governed by the quality of the underlying training data. In this work, a hybrid approach is presented combining analytical, numerical and data-based approaches efficiently to overcome the limitations of the individual techniques. As a result, explicit symbolic regression models are obtained, which are optimized on the basis of a numerically derived dataset. the power of this approach is demonstrated by a selected use-case. these highly accurate models may be implemented into any further application.

关键词： Training Analytical models Solid modeling Computational modeling Training data Predictive models Mathematical models

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Methods for Securing Routing Protocols in Ad-Hoc Networks

Methods for Securing Routing Protocols in Ad-Hoc Networks

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international symposium on symbolic and numeric algorithms for scientific computing (SYNASC)

作者： Ciobanu Costinela-Luminita Ciobanu Nicoleta Magdalena Department of Computer Science University of Pitesti Pitesti Romania Faculty of Mathematics and Computer Science/Department of Computer Science University of Pitesti Romania

the ad-hoc networks are wireless networks formed spontaneously between certain devices (computers, sensors, mobile phones and others) with limited resources (battery, memory, processing power) that doesn't have a central routing device (router) and so each node must ensure also this function. In addition, the network structure changes dynamically as needed. Because of these characteristics, the routing protocols developed for ad-hoc networks raise many security issues. In this paper we will review some of these problems and we propose some methods to improve their security. the main protocols studied in this paper are AODV (Ad-hoc On-Demand Distance Vector Routing) and OLSR (Optimized Link State Routing Protocol). We will also analyze the impact of our changes on the performance of the above listed protocols. the analyze will be performed using the OPNET Modeler network simulator.

关键词： Routing Routing protocols Security Peer-to-peer computing Mobile ad hoc networks

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An Application of the Shepard Operator in Image Reconstruction

An Application of the Shepard Operator in Image Reconstructi...

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international symposium on symbolic and numeric algorithms for scientific computing (SYNASC)

作者： Andra Malina Faculty of Mathematics and Computer Science Babeş-Bolyai UniversityTiberiu Popoviciu Institute of Numerical Analysis Romanian Academy Cluj-Napoca Romania

ISBN: (数字)9798331532833

ISBN: (纸本)9798331532840

We propose an application of the Shepard operator combined with two radial basis functions in image processing. this method aims to reconstruct damaged black-and-white or color images, considering both a global and a local approach. In the construction of the Shepard operator, we use the inverse quadratic and the inverse multiquadric radial basis functions.

关键词： scientific computing Noise Color Image restoration Image reconstruction

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Influence of Manual Inter-Observer Variability for the Performance of Deep Learning Models in Semantic Segmentation

Influence of Manual Inter-Observer Variability for the Perfo...

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international symposium on symbolic and numeric algorithms for scientific computing (SYNASC)

作者： Catalin Stoean Nebojsa Bacanin Ruxandra Stoean Leonard Ionescu Alina-Maria Gărău Cristina-Camelia Ghiţescu Department of Computer Science University of Craiova Artificial Intelligence and Machine Learning Team Romanian Institute of Science and Technology Romania Faculty of Informatics and Computing Singidunum University Belgrade Serbia Restoration and Conservation Lab Oltenia Museum History and Archaeology Section Craiova Romania

Deep learning models for semantic segmentation have expanded their application span from general objects to structures of interest in real-world tasks. the current paper discusses one such practical challenge, i.e. the delineation of corrosion compounds on microscope images taken at the surface of unrestored archaeological artefacts. Apart from the complexity of learning irregular shapes, the influence of the human manual annotations on model training becomes pivotal. the aim of the current paper thus becomes to measure the impact of interobserver variability on the segmentation of four copper corrosion compounds. the results support the need for rigorous guidelines in the manual establishment of the ground truth.

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Generalized Multisets Over Infinite Alphabets with Atoms

Generalized Multisets Over Infinite Alphabets with Atoms

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international symposium on symbolic and numeric algorithms for scientific computing (SYNASC)

作者： Andrei Alexandru Gabriel Ciobanu Romanian Academy Institute of Computer Science Iaşi Romania

ISBN: (数字)9798331532833

ISBN: (纸本)9798331532840

Hybrid sets are defined as multisets having also negative multiplicities, i.e. as functions from a crisp set to the group $\mathbb{Z}$ of all integers. In this short presentation, we consider a generalization of the hybrid sets by defining the group-valued multisets over $X$ as functions from $X$ to an arbitrary group $G$ . By involving the theory of finitely supported sets, we present finiteness properties of infinite group-valued multisets.

关键词： scientific computing Atoms

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Optimising Linear Regression for Modelling the Dynamic thermal Behaviour of Electrical Machines using NSGA-II, NSGA-III and MOEA/D

Optimising Linear Regression for Modelling the Dynamic Therm...

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international symposium on symbolic and numeric algorithms for scientific computing (SYNASC)

作者： Tiwonge Msulira Banda Alexandru-Ciprian Zăvoianu Andrei Petrovski Daniel Wöckinger Gerd Bramerdorfer National Subsea Centre School of Computing Robert Gordon University Aberdeen Scotland UK Institute for Electrical Drives and Power Electronics Johannes Kepler University Linz Austria

For engineers to create durable and effective electrical assemblies, modelling and controlling heat transfer in rotating electrical machines (such as motors) is crucial. In this paper, we compare the performance of three multi-objective evolutionary algorithms, namely NSGA-II, NSGA-III, and MOEA/D in finding the best trade-offs between data collection costs/effort and expected modelling errors when creating low-complexity Linear Regression (LR) models that can accurately estimate key motor component temperatures under various operational scenarios. the algorithms are integrated into a multi-objective thermal modelling strategy that aims to guide the discovery of models that are suitable for microcontroller deployment. Our findings show that while NSGA-II and NSGA-III yield comparably good optimisation outcomes, with a slight, but statistically significant edge for NSGA-II, the results achieved by MOEA/D for this use case are below par.

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Solar Flare Classification using Modified Metaheuristic Optimized XGBoost

Solar Flare Classification using Modified Metaheuristic Opti...

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international symposium on symbolic and numeric algorithms for scientific computing (SYNASC)

作者： Branislav Radomirovic Luka Jovanovic Catalin Stoean Miodrag Zivkovic Angelina Njegus Nebojsa Bacanin Faculty of Informatics and Computing Singidunum University Belgrade Serbia Faculty of Technical Sciences Singidunum University Belgrade Serbia Department of Computer Science University of Craiova Craiova Romania

the Sun has a significant effect on nearly everything in the solar system. While a relatively tame star, it is nevertheless prone to strong emissions of energy in the form of solar flares. Events frequency follows a cycle of approximately 11 years. At the peak of this cycle, events occur more often. Powerful events can even reach the Earth and cause magnetic storms that can disrupt radio communications, satellite trajectories, and navigation. Particular energetic events can even cause significant harm to power and telecommunications infrastructure. A need for a robust system capable of accurately handling classification is evident. this work proposes an approach based on extreme gradient boosting optimized via metaheuristic algorithms and applied to a real-world observation dataset. Outcomes have been compared to several modern optimization algorithms and the outcomes are promising. the results have been statistically validated as significant, and the best models analyzed to determine feature impacts on classifications.

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Pedestrian Trajectory Prediction Based on Tree Method using Graph Neural Networks

Pedestrian Trajectory Prediction Based on Tree Method using ...

引用

international symposium on symbolic and numeric algorithms for scientific computing (SYNASC)

作者： Bogdan Ilie Sighencea Department of Applied Electronics Politehnica University of Timișoara Timișoara Romania

Pedestrian trajectory prediction in real-world scenarios is a challenging task for several computer vision applications, such as autonomous driving, video surveillance, and robotic systems. this is not a trivial task due to the numerous potential trajectories. In this article, it provides a tree-based approach to handle this multimodal prediction challenge. the tree is designed based on the observed data and is also used to predict future trajectories. In particular, an individual's potential future trajectory is represented by the tree's root-to-leaf route. Compared to previous approaches that use implicit latent variables to describe possible future paths, the movement behaviors may be directly represented by the path in the tree (e.g., go straight and then turn left), and thus offer more socially suitable trajectories. the experimental results on the Eth, UCY, and Stanford Drone datasets show that this approach can exceed the performance of the state-of-the-art approaches. the solution is more efficient and compact, with a smaller model size and a higher accuracy, and delivers better results with reference to average displacement error (ADE) and final displacement error (FDE) metrics.

关键词： Measurement scientific computing Predictive models Video surveillance Prediction algorithms Graph neural networks Trajectory

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Primal Congestion Control algorithms for Multimedia Streams

Primal Congestion Control Algorithms for Multimedia Streams

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international symposium on symbolic and numeric algorithms for scientific computing (SYNASC)

作者： Adrian Sterca Department of Computer Science Babes Bolyai University Cluj-Napoca Romania

We investigate in this paper congestion control algorithms that are TCP-friendly and media-friendly at the same time, so they are more suitable for multimedia streaming than TCP's AIMD. We use in this investigation the optimization framework developed by Kelly et al. in. Kelly et al. derived two gradient-like algorithms, a primal algorithm and a dual one, to control the congestion in a computer network in an end-to-end way and to obtain optimal bandwidth allocation among competing sources. Starting with Kelly et. al's paper, several other papers proposed different variants of the original primal and dual algorithms, but none of these considers the specific characteristics of multimedia streams. the aim of this paper is to build window-based, primal congestion control algorithms for optimizing the perceived quality of multimedia streams in best-effort networks. We build these media-friendly primal congestion control algorithms using the following recipe: 1) first we construct a window-based congestion control algorithm that is TCP-friendly, but has a much more stable throughput and then 2) we shape this stable throughput according to media characteristics (e.g. bitrate). We present two such primal congestion control algorithms and prove their stability around the equilibrium.

关键词： Streaming media Multimedia systems Bit rate Internet Bandwidth Shape control Multimedia computing throughput Codecs Network servers

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