Showing papers in "Acta Polytechnica Hungarica in 2017"

Dynamic resource allocation in cloud computing

Abstract: Free to read on publisher's website Utilizing dynamic resource allocation for load balancing is considered as an important optimization process in cloud computing. In order to achieve maximum resource efficiency and scalability in a speedy manner this process is concerned with multiple objectives for an effective distribution of loads among virtual machines. In this realm,exploring new algorithms, as well as development of novel algorithms, is highly desired for technological advancement and continued progress in resource allocation application in cloud computing. Accordingly, this paper explores the application of two relatively new optimization algorithms and further proposes a hybrid algorithm for load balancing which can contribute well in maximizing the throughput of the cloud provider's network. The proposed algorithm is a hybrid of teaching-learning-based optimization algorithm (TLBO) and grey wolves optimization algorithm (GW). The hybrid algorithm performs more efficiently than utilizing every single one of these algorithms. Furthermore, it well balances the priorities and effectively considers load balancing based on time, cost, and avoidance of local optimum traps, which consequently leads to minimal amount of waiting time. To evaluate the effectiveness of the proposed algorithm, a comparison with the TLBO and GW algorithms is conducted and the experimental results are presented.

Fractional order impedance model to estimate glucose concentration : in vitro analysis

Abstract: This paper uses tools from fractional calculus such as Cole-Cole and fractional order impedance models for estimation of glucose concentration. The measured impedance is compared with two fractional order models and the simulation results show that Cole-Cole model has limitation and cannot capture the dynamics of the simulated environment. On the other hand, the fractional order model can follow the changes in impedance for several study cases. Model parameters are correlated with various conditions of the test environment. The results of these study cases show that the fractional order model is a suitable candidate for this particular application. The hypothesis tested in this paper provides new tools for glucose concentration monitoring and measurement.

Discrete-time implementation and experimental validation of a fractional order PD controller for vibration suppression in airplane wings

Abstract: Vibrations in airplane wings have a negative impact on the quality and safety of a flight. For this reason, active vibration suppression techniques are of extreme importance. In this paper, a smart beam is used as a simulator for the airplane wings and a fractional order PD controller is designed for active vibration mitigation. To implement the ideal fractional order controller on the smart beam unit, its digital approximation is required. In this paper, a new continuous-to-discrete-time operator is used to obtain the discrete-time approximation of the ideal fractional order PD controller. The efficiency and flexibility, as well as some guidelines for using this new operator, are given. The numerical examples show that high accuracy of approximation is obtained and that the proposed method can be considered as a suitable solution for obtaining the digital approximation of fractional order controllers. The experimental results demonstrate that the designed controller can significantly improve the vibration suppression in smart beams.

Managing big data using fuzzy sets by directed graph node similarity

Abstract: This paper proposes a novel algorithm for discovering similar nodes in very large directed graphs, with millions of nodes with billions of connections, which is based on the fuzzy set theory. The required input is a sample of representative nodes that are highly affiliated with some feature. This approach is practically verified on Twitter social network case study to discover influential Twitter users in the field of science.

Automatic detection of semantic primitives with bio-inspired, multi-objective, weighting algorithms

Abstract: This paper proposes the usage of computational techniques that allow for automatic analysis of the vocabulary contained in an explanatory dictionary. It is proposed for the extraction of a set of words, called semantic primitives, which are considered those allowing the creation of a system used to establish definitions in dictionaries. The proposed approach is based on the representation of a dictionary as a directed graph and the combination of a multi-objective differential evolution algorithm with the PageRank weighting algorithm. The differential evolution algorithm extracted a set of primitives that fulfill two objectives: minimize the set size and maximize its degree of representation (PageRank), allowing the creation of a computational dictionary without cycles in its definitions. We experimented with a RAE dictionary of Spanish. Our results present improvement over other algorithms that are representative of the state-of-the-art. O. Pichardo-Lagunas et al. Automatic Detection of Semantic Primitives with Bio-inspired, Multi-Objective, Weighting Algorithms – 114 –

Application of self-organizing maps for technological support of droplet epitaxy

Abstract: The subject of this paper is the self-organized grouping of droplet epitaxial III-Vbased nano-structures. For the nano-structure grouping, our developed algorithm called Quantum Structure Analyzer 1.0 is used. The operation of this software is based on the principles of the Kohonen Self-Organizing Network. Here, three possibilities for nanostructured groupings are shown. On one hand, we examine the classification of nanostructures with Kohonen Self-Organizing Maps, on the other hand, fuzzy inference systems are applied for the same goal. In the case of the fuzzy methods two approaches are examined in detail. According to the first fuzzy inference approach, the shape factor is calculated from the size of nanostructures. According to the second fuzzy inference approach, the shape factor calculation is based on the controllable parameters of the growth process (eg. pressure and the temperature of the substrate).

Reproducibility Analysis of Scientific Workflows

Abstract: Scientific workflows are efficient tools for specifying and automating compute and data intensive in-silico experiments. An important challenge related to their usage is their reproducibility. In order to make it reproducible, many factors have to be investigated which can influence and even prevent this process: the missing descriptions and samples; the missing provenance data about the environmental parameters and the data dependencies; the dependencies of executions which are based on special hardware, changing or volatile third party services or random generated values. Some of these factors (called dependencies) can be eliminated by careful design or by huge resource usage but most of them cannot be bypassed. Our investigation deals with the critical dependencies of execution. In this paper we set up a mathematical model to evaluate the results of the workflow in addition we provide a mechanism to make the workflow reproducible based on provenance data and statistical tools.

Robust Control of Single-Mast Stacker Cranes

Abstract: The stacker cranes in automated storage/retrieval systems (AS/RS) of warehouses often have very high dynamical loads. These dynamical loads may generate harmful mast vibrations in the frame structure of stacker cranes which can reduce the stability and positioning accuracy of these machines. The aim of this paper is to develop controller design methods which have proper reference signal tracking and mast-vibration attenuation properties. First, the dynamic modeling of single-mast stacker cranes by means of multibody modeling approach is summarized. Based on this modeling technique a H∞ and a robust control design method are proposed for achieving the appointed purposes. The analyses of the controlled systems are carried out by time domain simulations.

Infectious hospital agents: A HAI spreading simulation framework

Abstract: Infectious Hospital Agents (IHA) is an individual-based simulation framework that is able to model wide range of infection spreading scenarios in the hospital environment. The simulations are agent-based simulations driven by stochastic events, the evolution of the model is tracked in discrete time. Our aim was to build a general, customisable and extensible simulation environment for the domain of Hospital-Associated Infections (HAIs). The system is designed in Object Oriented fashion, and the implementation is in C++. In this paper, the authors describe the motivations and the background of the framework, sketch the conceptual framework, and present a demonstration example.

Assessment of the Sensory and Moisturizing Properties of Emulsions with Hemp Oil

Abstract: The aims of this work were a sensory analysis, an evaluation of moistening properties and establishment of emulsions stability. Emulsions were prepared with two variable parameters (hemp oil content and time of homogenization). 15 respondents assessed emulsions sensory and skin moisturizing properties. Kleeman’s optimizing method was used to designate the most stable emulsion system with the variable parameters. Taking into consideration all properties of the presented emulsions, emulsion V (50g of hemp oil and homogenized for 6 minutes) was found to be the optimum composition with the best moistening and sensory properties. After the application of this emulsion, the skin was highly moistened. Consistency of the emulsions was homogeneous and free from clotting. According to Kleeman’s method, emulsion V was also confirmed as the most optimum variant of the emulsion. The work confirmed that hemp oil can be successfully used as a component for cosmetic emulsions.

Influence of Stress State Conditions on Densification Behavior of Titanium Sponge

Abstract: The paper discusses the material compaction process under various types of stress conditions based on the simulation of the multiaxial compression process of powdered titanium sponge. The finite element model of the multiaxial compression process made it possible to apply both radial and axial pressure independently from one another. Titanium sponge subjected to reversible thermo-hydrogen processing was used as the research material. For the description of the material plasticity condition, the modified Drucker–Prager Cap plasticity model was used, implemented in Abaqus.

Limiting static and dynamic characteristics of an induction motor under frequency vector control

Abstract: Static and dynamic characteristics of an induction motor (IM) under frequency vector control are reviewed. Limiting static characteristics enabling to determine the limits of an automatic electric drive, as well as regions of short-term and admissible continuous performance of an induction motor under frequency vector control are presented. Recommendations on the choice of maximum phase voltage of an inverter, DC link voltage of a frequency converter and supply voltage of an induction motor as well as possible ways to reach maximum angular velocity of an induction motor under frequency vector control are suggested.

Non-destructive analysis of explanted coronary artery stents

Abstract: Endovascular stents are used to effectively treat atherosclerosis during angioplasty. Nowadays, this surgery is performed on younger and younger patients, so the stent can be in the body for over 30 years. The stent cannot be removed from the patient, so the in vivo stability of the stent and the effects of the human organism on the stent can only be investigated on postmortem explanted stents. Therefore, this study deals with the non-destructive investigation of explanted coronary stents. Our goal was to determine the causes of visible damages and to measure the changes in the technical state.