Search results for: computational methods

Authors: Temidayo Otunniyi

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This paper presents a low computational channelization algorithm for the multi-standards platform using poly phase implementation of a critically sampled hybrid Trigonometry generalized Discrete Fourier Transform, (HGDFT). An HGDFT channelization algorithm exploits the orthogonality of two trigonometry Fourier functions, together with the properties of Quadrature Mirror Filter Bank (QMFB) and Exponential Modulated filter Bank (EMFB), respectively. HGDFT shows improvement in its implementation in terms of high reconfigurability, lower filter length, parallelism, and medium computational activities. Type 1 and type 111 poly phase structures are derived for real-valued HGDFT modulation. The design specifications are decimated critically and over-sampled for both single and multi standards receiver platforms. Evaluating the performance of oversampled single standard receiver channels, the HGDFT algorithm achieved 40% complexity reduction, compared to 34% and 38% reduction in the Discrete Fourier Transform (DFT) and tree quadrature mirror filter (TQMF) algorithm. The parallel generalized discrete Fourier transform (PGDFT) and recombined generalized discrete Fourier transform (RGDFT) had 41% complexity reduction and HGDFT had a 46% reduction in oversampling multi-standards mode. While in the critically sampled multi-standard receiver channels, HGDFT had complexity reduction of 70% while both PGDFT and RGDFT had a 34% reduction.

Keywords: software defined radio, channelization, critical sample rate, over-sample rate

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Authors: Kunal Shah, Swati Patel

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Many real world problems involve data which can be considered as multi-label data streams. Efficient methods exist for multi-label classification in non streaming scenarios. However, learning in evolving streaming scenarios is more challenging, as the learners must be able to adapt to change using limited time and memory. Classification is used to predict class of unseen instance as accurate as possible. Multi label classification is a variant of single label classification where set of labels associated with single instance. Multi label classification is used by modern applications, such as text classification, functional genomics, image classification, music categorization etc. This paper introduces the task of multi-label classification, methods for multi-label classification and evolution measure for multi-label classification. Also, comparative analysis of multi label classification methods on the basis of theoretical study, and then on the basis of simulation was done on various data sets.

Keywords: binary relevance, concept drift, data stream mining, MLSC, multiple window with buffer

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Authors: Jonghyuk Yoon, Hyoungwoon Song, Youngbae Kim, Eunju Kim

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Recently, with the rapid growth of semiconductor industry, lots of interests have been focused on after treatment system that remove the polluted gas produced from semiconductor manufacturing process, and a wet scrubber is the one of the widely used system. When it comes to mechanism of removing the gas, the polluted gas is removed firstly by chemical reaction in a reactor part. After that, the polluted gas stream is brought into contact with the scrubbing liquid, by spraying it with the liquid. Effective design of the reactor part inside the wet scrubber is highly important since removal performance of the polluted gas in the reactor plays an important role in overall performance and stability. In the present study, a CFD (Computational Fluid Dynamics) analysis was performed to figure out the thermal and flow characteristics inside unit a reactor of wet scrubber. In order to verify the numerical result, temperature distribution of the numerical result at various monitoring points was compared to the experimental result. The average error rates (12~15%) between them was shown and the numerical result of temperature distribution was in good agreement with the experimental data. By using validated numerical method, the effect of the reactor geometry on heat transfer rate was also taken into consideration. Uniformity of temperature distribution was improved about 15%. Overall, the result of present study could be useful information to identify the fluid behavior and thermal performance for various scrubber systems. This project is supported by the ‘R&D Center for the reduction of Non-CO₂ Greenhouse gases (RE201706054)’ funded by the Korea Ministry of Environment (MOE) as the Global Top Environment R&D Program.

Keywords: semiconductor, polluted gas, CFD (Computational Fluid Dynamics), wet scrubber, reactor

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Authors: Siqi Qiu, Yijian Zheng, Xin Guo Ming

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In many reliability and risk analysis, failures of components are supposed to be independent. However, in reality, the ignorance of failure dependencies among components may render the results of reliability and risk analysis incorrect. There are two principal ways to incorporate failure dependencies in system reliability and risk analysis: implicit and explicit methods. In the implicit method, failure dependencies can be modeled by joint probabilities, correlation values or conditional probabilities. In the explicit method, certain types of dependencies can be modeled in a fault tree as mutually independent basic events for specific component failures. In this paper, explicit and implicit methods based on BDD will be proposed to evaluate the reliability of systems considering failure dependencies. The obtained results prove the equivalence of the proposed implicit and explicit methods. It is found that the consideration of failure dependencies decreases the reliability of systems. This observation is intuitive, because more components fail due to failure dependencies. The consideration of failure dependencies helps designers to reduce the dependencies between components during the design phase to make the system more reliable.

Keywords: reliability assessment, risk assessment, failure dependencies, binary decision diagram

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Authors: Hamza Nejib, Okba Taouali

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This paper presents two of the most knowing kernel adaptive filtering (KAF) approaches, the kernel least mean squares and the kernel recursive least squares, in order to predict a new output of nonlinear signal processing. Both of these methods implement a nonlinear transfer function using kernel methods in a particular space named reproducing kernel Hilbert space (RKHS) where the model is a linear combination of kernel functions applied to transform the observed data from the input space to a high dimensional feature space of vectors, this idea known as the kernel trick. Then KAF is the developing filters in RKHS. We use two nonlinear signal processing problems, Mackey Glass chaotic time series prediction and nonlinear channel equalization to figure the performance of the approaches presented and finally to result which of them is the adapted one.

Keywords: online prediction, KAF, signal processing, RKHS, Kernel methods, KRLS, KLMS

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Authors: Michael Williams

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The ability to control a flowing well is of the utmost important. During the kill phase, heavy weight kill mud is circulated around the well. While increasing bottom hole pressure near wellbore formation, the damage is increased. The addition of high density spherical objects has the potential to minimise this near wellbore damage, increase bottom hole pressure and reduce operational time to kill the well. This operational time saving is seen in the rapid deployment of high density spherical objects instead of building high density drilling fluid. The research aims to model the well kill process using a Computational Fluid Dynamics software. A model has been created as a proof of concept to analyse the flow of micron sized spherical objects in the drilling fluid. Initial results show that this new methodology of spherical objects in drilling fluid agrees with traditional stream lines seen in non-particle flow. Additional models have been created to demonstrate that areas of higher flow rate around the bit can lead to increased probability of wash out of formations but do not affect the flow of micron sized spherical objects. Interestingly, areas that experience dimensional changes such as tool joints and various BHA components do not appear at this initial stage to experience increased velocity or create areas of turbulent flow, which could lead to further borehole stability. In conclusion, the initial models of this novel well control methodology have not demonstrated any adverse flow patterns, which would conclude that this model may be viable under field conditions.

Keywords: well control, fluid mechanics, safety, environment

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Authors: Omid Tavakol, Mahnaz Gholami

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Introduction : In this oral presentation the main goal is discussing immediate loading in dental implants , from treatment planning and surgical guide designing to delivery , follow up and occlusal consideration . Methods and materials : first of all systematic reviews about immediate loading will be considered . besides , a comparison will be made between immediate loading and conventional loading in terms of success rate and complications . After that different methods , prosthetic options and materials best used in immediate loading will be explained. Particularly multi unit abutments and their mechanism of function will be explained .Digital impressions and designing the temporaries is the next topic we are to explicate .Next issue is the differences between single unit , multiple unit and full arch implantation in immediate loading .Following we are going to describe methods for tissue engineering and papilla formation after extraction . Last slides are about a full mouth rehabilitation via immediate loading technique from surgical designing to follow up .At the end we would talk about potential complications , how to prevent from occurrence and what to do if we face up with .

Keywords: guided surgery, digital implantology, immediate loading, digital dentistry

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Authors: Samaneh Yavari, Christiane Pferrer, Elisabeth Engelke, Alexander Starke, Juergen Rehage

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Background: Three nociceptive thresholds of thermal, electrical, and mechanical thresholds commonly use to evaluate the local anesthesia in many species, for instance, cow, horse, cat, dog, rabbit, and so on. Due to the lack of investigations to evaluate and/or validate such those nociceptive thresholds, our plan was the comparison of two-foot local anesthesia methods of Intravenous Regional Anesthesia (IVRA) and our modified four-point Nerve Block Anesthesia (NBA). Materials and Methods: Eight healthy nonpregnant nondairy Holstein Frisian cows in a cross-over study design were selected for this study. All cows divided into two different groups to receive two local anesthesia techniques of IVRA and our modified four-point NBA. Three thermal, electrical, and mechanical force and pinpricks were applied to evaluate the quality of local anesthesia methods before and after local anesthesia application. Results: The statistical evaluation demonstrated that our four-point NBA has a qualification to select as a standard foot local anesthesia. However, the recorded results of our study revealed no significant difference between two groups of local anesthesia techniques of IVRA and modified four-point NBA related to quality and duration of anesthesia stimulated by electrical, mechanical and thermal nociceptive stimuli. Conclusion and discussion: All three nociceptive threshold stimuli of electrical, mechanical and heat nociceptive thresholds can be applied to measure and evaluate the efficacy of foot local anesthesia of dairy cows. However, our study revealed no superiority of those three nociceptive methods to evaluate the duration and quality of bovine foot local anesthesia methods. Veterinarians to investigate the duration and quality of their selected anesthesia method can use any of those heat, mechanical, and electrical methods.

Keywords: mechanical, thermal, electrical threshold, IVRA, NBA, hind limb, dairy cow

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Authors: Thang Minh Le, Hadi Khabbaz

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The coefficient of consolidation is a parameter governing the rate at which saturated soil particularly clay undergoes consolidation when subjected to an increase in pressure. The rate and amount of compression in soil varies with the rate that pore water is lost; and hence depends on soil permeability. Over many years, various methods have been proposed to determine the coefficient of consolidation, cv, which is an indication of the rate of foundation settlement on soft ground. However, defining this parameter is often problematic and heavily relies on graphical techniques, which are subject to some uncertainties. This paper initially presents an overview of many well-established methods to determine the vertical coefficient of consolidation from the incremental loading consolidation tests. An array of consolidation tests was conducted on the undisturbed clay samples, collected at various depths from a site in Nakdong river delta, Busan, South Korea. The consolidation test results on these soft sensitive clay samples were employed to evaluate the targeted methods to predict the settlement rate of Busan clay. In relationship of time-displacement-velocity, a total of 3 method groups from 10 common procedures were classified and compared together. Discussions on study results will be also provided.

Keywords: Busan clay, coefficient of consolidation, constant rate of strain, incremental loading

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Authors: E. G. Karvelas, C. Liosis, A. Theodorakakos, T. E. Karakasidis

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Magnetic navigation of the drug inside the human vessels is a very important concept since the drug is delivered to the desired area. Consequently, the quantity of the drug required to reach therapeutic levels is being reduced while the drug concentration at targeted sites is increased. Magnetic navigation of drug agents can be achieved with the use of magnetic nanoparticles where anti-tumor agents are loaded on the surface of the nanoparticles. The magnetic field that is required to navigate the particles inside the human arteries is produced by a magnetic resonance imaging (MRI) device. The main factors which influence the efficiency of the usage of magnetic nanoparticles for biomedical applications in magnetic driving are the size and the magnetization of the biocompatible nanoparticles. In this study, a computational platform for the simulation of the optimal gradient magnetic fields for the navigation of magnetic nanoparticles inside a carotid artery is presented. For the propulsion model of the particles, seven major forces are considered, i.e., the magnetic force from MRIs main magnet static field as well as the magnetic field gradient force from the special propulsion gradient coils. The static field is responsible for the aggregation of nanoparticles, while the magnetic gradient contributes to the navigation of the agglomerates that are formed. Moreover, the contact forces among the aggregated nanoparticles and the wall and the Stokes drag force for each particle are considered, while only spherical particles are used in this study. In addition, gravitational forces due to gravity and the force due to buoyancy are included. Finally, Van der Walls force and Brownian motion are taken into account in the simulation. The OpenFoam platform is used for the calculation of the flow field and the uncoupled equations of particles' motion. To verify the optimal gradient magnetic fields, a covariance matrix adaptation evolution strategy (CMAES) is used in order to navigate the particles into the desired area. A desired trajectory is inserted into the computational geometry, which the particles are going to be navigated in. Initially, the CMAES optimization strategy provides the OpenFOAM program with random values of the gradient magnetic field. At the end of each simulation, the computational platform evaluates the distance between the particles and the desired trajectory. The present model can simulate the motion of particles when they are navigated by the magnetic field that is produced by the MRI device. Under the influence of fluid flow, the model investigates the effect of different gradient magnetic fields in order to minimize the distance of particles from the desired trajectory. In addition, the platform can navigate the particles into the desired trajectory with an efficiency between 80-90%. On the other hand, a small number of particles are stuck to the walls and remains there for the rest of the simulation.

Keywords: artery, drug, nanoparticles, navigation

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Authors: Saeed Delara, Kendra MacKay

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Varying methodologies are considered for pile design for both Russian and Western approaches. Although both approaches rely on toe and side frictional resistances, different calculation methods are proposed to estimate pile capacity. The Western approach relies on compactness (internal friction angle) of soil for cohesionless soils and undrained shear strength for cohesive soils. The Russian approach relies on grain size for cohesionless soils and liquidity index for cohesive soils. Though most recommended methods in the Western approaches are relatively simple methods to predict pile settlement, the Russian approach provides a detailed method to estimate single pile and pile group settlement. Details to calculate pile axial capacity and settlement using the Russian and Western approaches are discussed and compared against field test results.

Keywords: pile capacity, pile settlement, Russian approach, western approach

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Authors: Vusumzi E. Pakade, Themba D. Ntuli, Augustine E. Ofomaja

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Macadamia nutshell biosorbents treated in three different methods (raw Macadamia nutshell powder (RMN), acid-treated Macadamia nutshell (ATMN) and base-treated Macadamia nutshell (BTMN)) were investigated for the adsorption of Cr(VI) from aqueous solutions. Fourier transform infrared spectroscopy (FT-IR) spectra of free and Cr(VI)-loaded sorbents as well as thermogravimetric analysis (TGA) revealed that the acid and base treatments modified the surface properties of the sorbents. The optimum conditions for the adsorption of Cr(VI) by sorbents were pH 2, contact time 10 h, adsorbent dosage 0.2 g L-1, and concentration 100 mg L-1. The different treatment methods altered the surface characteristics of the sorbents and produced different maximum binding capacities of 42.5, 40.6 and 37.5 mg g-1 for RMN, ATMN and BTMN, respectively. The data was fitted into the Langmuir, Freundlich, Redlich-Peterson and Sips isotherms. No single model could clearly explain the data perhaps due to the complexity of process taking place. The kinetic modeling results showed that the process of Cr(VI) biosorption with Macadamia sorbents was better described by a process of chemical sorption in pseudo-second order. These results showed that the three treatment methods yielded different surface properties which then influenced adsorption of Cr(VI) differently.

Keywords: biosorption, chromium(VI), isotherms, Macadamia, reduction, treatment

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Authors: Mostafa Mjahed

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This paper concerns the control of a nonlinear system using two different methods, reference model and genetic algorithm. The quadcopter is a nonlinear unstable system, which is a part of aerial robots. It is constituted by four rotors placed at the end of a cross. The center of this cross is occupied by the control circuit. Its motions are governed by six degrees of freedom: three rotations around 3 axes (roll, pitch and yaw) and the three spatial translations. The control of such system is complex, because of nonlinearity of its dynamic representation and the number of parameters, which it involves. Numerous studies have been developed to model and stabilize such systems. The classical PID and LQ correction methods are widely used. If the latter represent the advantage to be simple because they are linear, they reveal the drawback to require the presence of a linear model to synthesize. It also implies the complexity of the established laws of command because the latter must be widened on all the domain of flight of these quadcopter. Note that, if the classical design methods are widely used to control aeronautical systems, the Artificial Intelligence methods as genetic algorithms technique receives little attention. In this paper, we suggest comparing two PID design methods. Firstly, the parameters of the PID are calculated according to the reference model. In a second phase, these parameters are established using genetic algorithms. By reference model, we mean that the corrected system behaves according to a reference system, imposed by some specifications: settling time, zero overshoot etc. Inspired from the natural evolution of Darwin's theory advocating the survival of the best, John Holland developed this evolutionary algorithm. Genetic algorithm (GA) possesses three basic operators: selection, crossover and mutation. We start iterations with an initial population. Each member of this population is evaluated through a fitness function. Our purpose is to correct the behavior of the quadcopter around three axes (roll, pitch and yaw) with 3 PD controllers. For the altitude, we adopt a PID controller.

Keywords: quadcopter, genetic algorithm, PID, fitness, model, control, nonlinear system

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Authors: Olaide O. Wahab, Lukman O. Olasunkanmi, Krishna K. Govender, Penny P. Govender

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The economic and environmental challenges associated with azo disperse dyes applications are due to poor aqueous solubility and low degradation tendency which stems from low chemical reactivity. Poor aqueous solubility property of this group of dyes necessitates the use of dispersing agents which increase operational costs and also release toxic chemical components into the environment, while their low degradation tendency is due to the high stability of the azo functional group (-N=N-) in their chemical structures. To address these problems, this study investigated theoretically the effects of some polar substituents on the aqueous solubility and reactivity properties of disperse yellow (DY) 119 dye with a view to theoretically develop new azo disperse dyes with improved solubility in water and higher degradation tendency in the environment using DMol³ computational code. All calculations were carried out using the Becke and Perdew version of Volsko-Wilk-Nusair (VWN-BP) level of density functional theory in conjunction with double numerical basis set containing polarization function (DNP). The aqueous solubility determination was achieved with conductor-like screening model for realistic solvation (COSMO-RS) in conjunction with known empirical solubility model, while the reactivity was predicted using frontier molecular orbital calculations. Most of the new derivatives studied showed evidence of higher aqueous solubility and degradation tendency compared to the parent dye. We conclude that these derivatives are promising alternative dyes for more economic and environmental benign dyeing practice and therefore recommend them for synthesis.

Keywords: aqueous solubility, azo disperse dye, degradation, disperse yellow 119, DMol³, reactivity

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Authors: Jerry Gyimah, Ernest Kissi, Safowaa Osei-Tutu, Charles Dela Adobor, Theophilus Adjei-Kumi, Ernest Osei-Tutu

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Price fluctuation contract is imperative and of paramount essence, in the construction industry as it provides adequate relief and cushioning for changes in the prices of input resources during construction. As a result, several methods have been devised to better help in arriving at fair recompense in the event of price changes. However, stakeholders often appear not to be satisfied with the existing methods of fluctuation evaluation, ostensibly because of the challenges associated with them. The aim of this study was to identify the challenges to the usage of building construction cost indices in Ghana. Data was gathered from contractors and quantity surveying firms. The study utilized a survey questionnaire approach to elicit responses from the contractors and the consultants. Data gathered was analyzed scientifically, using the relative importance index (RII) to rank the problems associated with the existing methods. The findings revealed the following, among others, late release of data, inadequate recovery of costs, and work items of interest not included in the published indices as the main challenges of the existing methods. Findings provide useful lessons for policymakers and practitioners in decision making towards the usage and improvement of available indices.

Keywords: building construction cost indices, challenges, usage, Ghana

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Authors: Jaehong Yu, Seoung Bum Kim

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Clustering analysis can facilitate the extraction of intrinsic patterns in a dataset and reveal its natural groupings without requiring class information. For effective clustering analysis in high dimensional datasets, unsupervised dimensionality reduction is an important task. Unsupervised dimensionality reduction can generally be achieved by feature extraction or feature selection. In many situations, feature selection methods are more appropriate than feature extraction methods because of their clear interpretation with respect to the original features. The unsupervised feature selection can be categorized as feature subset selection and feature ranking method, and we focused on unsupervised feature ranking methods which evaluate the features based on their importance scores. Recently, several unsupervised feature ranking methods were developed based on ensemble approaches to achieve their higher accuracy and stability. However, most of the ensemble-based feature ranking methods require the true number of clusters. Furthermore, these algorithms evaluate the feature importance depending on the ensemble clustering solution, and they produce undesirable evaluation results if the clustering solutions are inaccurate. To address these limitations, we proposed an ensemble-based feature ranking method with random subspace and multiple-k ensemble (FRRM). The proposed FRRM algorithm evaluates the importance of each feature with the random subspace ensemble, and all evaluation results are combined with the ensemble importance scores. Moreover, FRRM does not require the determination of the true number of clusters in advance through the use of the multiple-k ensemble idea. Experiments on various benchmark datasets were conducted to examine the properties of the proposed FRRM algorithm and to compare its performance with that of existing feature ranking methods. The experimental results demonstrated that the proposed FRRM outperformed the competitors.

Keywords: clustering analysis, multiple-k ensemble, random subspace-based feature evaluation, unsupervised feature ranking

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Authors: Kerstin Grunden, Ann Svensson, Berit Forsman, Christina Karlsson, Ayman Obeid

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The research question of the article is to explore whether the dialogue meetings method could be relevant for reflective learning among researchers and practitioners when welfare technology should be implemented in municipalities, or not. A testbed was planned to be implemented in a retirement home in a Swedish municipality, and the practitioners worked with a pre-study of that testbed. In the article, the dialogue between the researchers and the practitioners in the dialogue meetings is described and analyzed. The potential of dialogue meetings as an arena for learning and reflection among researchers and practitioners is discussed. The research methodology approach is participatory action research with mixed methods (dialogue meetings, focus groups, participant observations). The main findings from the dialogue meetings were that the researchers learned more about the use of traditional research methods, and the practitioners learned more about how they could improve their use of the methods to facilitate change processes in their organization. These findings have the potential both for the researchers and the practitioners to result in more relevant use of research methods in change processes in organizations. It is concluded that dialogue meetings could be relevant for reflective learning among researchers and practitioners when welfare technology should be implemented in a health care organization.

Keywords: dialogue meetings, implementation, reflection, test bed, welfare technology, participatory action research

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Authors: Takeshi Takemoto, Naoya Suzuki, Naohisa Takagaki, Satoru Komori, Masako Terui, George Truscott

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Drag coefficient is an important parameter in order to correctly estimate the air-sea momentum flux. However, The parameterization of the drag coefficient hasn’t been established due to the variation in the field data. Instead, a number of drag coefficient model formulae have been proposed, even though almost all these models haven’t discussed the extreme wind speed range. With regards to such models, it is unclear how the drag coefficient changes in the extreme wind speed range as the wind speed increased. In this study, we investigated the effect of the drag coefficient models concerning the air-sea momentum flux in the extreme wind range on a global scale, comparing two different drag coefficient models. Interestingly, one model didn’t discuss the extreme wind speed range while the other model considered it. We found that the difference of the models in the annual global air-sea momentum flux was small because the occurrence frequency of strong wind was approximately 1% with a wind speed of 20m/s or more. However, we also discovered that the difference of the models was shown in the middle latitude where the annual mean air-sea momentum flux was large and the occurrence frequency of strong wind was high. In addition, the estimated data showed that the difference of the models in the drag coefficient was large in the extreme wind speed range and that the largest difference became 23% with a wind speed of 35m/s or more. These results clearly show that the difference of the two models concerning the drag coefficient has a significant impact on the estimation of a regional air-sea momentum flux in an extreme wind speed range such as that seen in a tropical cyclone environment. Furthermore, we estimated each air-sea momentum flux using several kinds of drag coefficient models. We will also provide data from an observation tower and result from CFD (Computational Fluid Dynamics) concerning the influence of wind flow at and around the place.

Keywords: air-sea interaction, drag coefficient, air-sea momentum flux, CFD (Computational Fluid Dynamics)

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Authors: Tanit Daniel Jodar Vecina, Adriane Prisco Petry

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The shape of the wind velocity profile changes according to local features of terrain shape and roughness, which are parameters responsible for defining the Atmospheric Boundary Layer (ABL) profile. Air flow characteristics over and around landforms, such as hills, are of considerable importance for applications related to Wind Farm and Turbine Engineering. The air flow is accelerated on top of hills, which can represent a decisive factor for Wind Turbine placement choices. The present work focuses on the study of ABL behavior as a function of slope and surface roughness of hill-shaped landforms, using the Computational Fluid Dynamics (CFD) to build wind velocity and turbulent intensity profiles. Reynolds-Averaged Navier-Stokes (RANS) equations are closed using the SST k-ω turbulence model; numerical results are compared to experimental data measured in wind tunnel over scale models of the hills under consideration. Eight hill models with slopes varying from 25° to 68° were tested for two types of terrain categories in 2D and 3D, and two analytical codes are used to represent the inlet velocity profiles. Numerical results for the velocity profiles show differences under 4% when compared to their respective experimental data. Turbulent intensity profiles show maximum differences around 7% when compared to experimental data; this can be explained by not being possible to insert inlet turbulent intensity profiles in the simulations. Alternatively, constant values based on the averages of the turbulent intensity at the wind tunnel inlet were used.

Keywords: Atmospheric Boundary Layer, Computational Fluid Dynamic (CFD), Numerical Modeling, Wind Tunnel

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Authors: Stefan Bauer, Josef Frysak

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According to the scientific information management literature, the improper use of information technology (e.g. personal computers) by employees are one main cause for operational and information security loss events. Therefore, organizations implement information security awareness programs to increase employees’ awareness to further prevention of loss events. However, in many cases these information security awareness programs consist of conventional delivery methods like posters, leaflets, or internal messages to make employees aware of information security policies. We assume that a viral information security awareness video might be more effective medium than conventional methods commonly used by organizations. The purpose of this research is to develop a viral video artifact to improve employee security behavior concerning information technology.

Keywords: information security awareness, delivery methods, viral videos, employee security behavior

Procedia PDF Downloads 542

Authors: Jiří F. Urbánek, David Král

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Small and Middle Enterprises (SME) have a specific mission, characteristics, and behavior in global business competitive environments. They must respect policy, rules, requirements and standards in all their inherent and outer processes of supply - customer chains and networks. Paper aims and purposes are to introduce computational assistance, which enables us the using of prevailing operation system MS Office (SmartArt...) for mathematical models, using DYVELOP (Dynamic Vector Logistics of Processes) method. It is providing for SMS´s global environment the capability and profit to achieve its commitment regarding the effectiveness of the quality management system in customer requirements meeting and also the continual improvement of the organization’s and SME´s processes overall performance and efficiency, as well as its societal security via continual planning improvement. DYVELOP model´s maps - the Blazons are able mathematically - graphically express the relationships among entities, actors, and processes, including the discovering and modeling of the cycling cases and their phases. The blazons need live PowerPoint presentation for better comprehension of this paper mission – added value analysis. The crisis management of SMEs is obliged to use the cycles for successful coping of crisis situations.  Several times cycling of these cases is a necessary condition for the encompassment of the both the emergency event and the mitigation of organization´s damages. Uninterrupted and continuous cycling process is a good indicator and controlling actor of SME continuity and its sustainable development advanced possibilities.

Keywords: blazons, computational assistance, DYVELOP method, small and middle enterprises

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Authors: Shazi Shah Jabeen, Ajay Jesse Thomas

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The study is aimed at understanding the learning trends of students who opt for online language courses and to assess the effectiveness of the same. Multiple factors including use of the latest available technology and the skills that are trained by these online methods have been assessed. An attempt has been made to answer how each of the various language skills is trained online and how effective the online methods are compared to the classroom methods when students interact with peers and instructor. A mixed method research design was followed for collecting information for the study where a survey by means of a questionnaire and in-depth interviews with a number of respondents were undertaken across the various institutes and study centers located in the United Arab Emirates. The questionnaire contained 19 questions which included 7 sub-questions. The study revealed that the students find learning with an instructor to be a lot more effective than learning alone in an online environment. They prefer classroom environment more than the online setting for language learning.

Keywords: effectiveness, language, online learning, skills

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Authors: I. V. Pinto, M. R. Sooriyarachchi

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It can be frequently observed that the data arising in our environment have a hierarchical or a nested structure attached with the data. Multilevel modelling is a modern approach to handle this kind of data. When multilevel modelling is combined with a binary response, the estimation methods get complex in nature and the usual techniques are derived from quasi-likelihood method. The estimation methods which are compared in this study are, marginal quasi-likelihood (order 1 & order 2) (MQL1, MQL2) and penalized quasi-likelihood (order 1 & order 2) (PQL1, PQL2). A statistical model is of no use if it does not reflect the given dataset. Therefore, checking the adequacy of the fitted model through a goodness-of-fit (GOF) test is an essential stage in any modelling procedure. However, prior to usage, it is also equally important to confirm that the GOF test performs well and is suitable for the given model. This study assesses the suitability of the GOF test developed for binary response multilevel models with respect to the method used in model estimation. An extensive set of simulations was conducted using MLwiN (v 2.19) with varying number of clusters, cluster sizes and intra cluster correlations. The test maintained the desirable Type-I error for models estimated using PQL2 and it failed for almost all the combinations of MQL. Power of the test was adequate for most of the combinations in all estimation methods except MQL1. Moreover, models were fitted using the four methods to a real-life dataset and performance of the test was compared for each model.

Keywords: goodness-of-fit test, marginal quasi-likelihood, multilevel modelling, penalized quasi-likelihood, power, quasi-likelihood, type-I error

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Authors: Muhsin Kizhisseri, Jorg Schluter, Saleh Gharie

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Atherosclerosis is the main reason of stroke, which is one of the deadliest diseases in the world. The carotid artery in the brain is the prominent location for atherosclerotic progression, which hinders the blood flow into the brain. The inclusion of computational fluid dynamics (CFD) into the diagnosis cycle to understand the hemodynamics of the patient-specific carotid artery can give insights into stroke prediction. Realistic outlet boundary conditions are an inevitable part of the numerical simulations, which is one of the major factors in determining the accuracy of the CFD results. The Windkessel model-based outlet boundary conditions can give more realistic characteristics of the distal vascular branches of the carotid artery, such as the resistance to the blood flow and compliance of the distal arterial walls. This study aims to find the most influential distal branches of the carotid artery by using the Windkessel model parameters in the outlet boundary conditions. The parametric study approach to Windkessel model parameters can include the geometrical features of the distal branches, such as radius and length. The incorporation of the variations of the geometrical features of the major distal branches such as the middle cerebral artery, anterior cerebral artery, and ophthalmic artery through the Windkessel model can aid in identifying the most influential distal branch in the carotid artery. The results from this study can help physicians and stroke neurologists to have a more detailed and accurate judgment of the patient's condition.

Keywords: stroke, carotid artery, computational fluid dynamics, patient-specific, Windkessel model, distal vascular branches

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Authors: Piotr A. Kowalski, Kasper Sapala, Wiktor Warchalowski

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PM10 is a suspended dust that primarily has a negative effect on the respiratory system. PM10 is responsible for attacks of coughing and wheezing, asthma or acute, violent bronchitis. Indirectly, PM10 also negatively affects the rest of the body, including increasing the risk of heart attack and stroke. Unfortunately, Poland is a country that cannot boast of good air quality, in particular, due to large PM concentration levels. Therefore, based on the dense network of Airly sensors, it was decided to deal with the problem of prediction of suspended particulate matter concentration. Due to the very complicated nature of this issue, the Machine Learning approach was used. For this purpose, Convolution Neural Network (CNN) neural networks have been adopted, these currently being the leading information processing methods in the field of computational intelligence. The aim of this research is to show the influence of particular CNN network parameters on the quality of the obtained forecast. The forecast itself is made on the basis of parameters measured by Airly sensors and is carried out for the subsequent day, hour after hour. The evaluation of learning process for the investigated models was mostly based upon the mean square error criterion; however, during the model validation, a number of other methods of quantitative evaluation were taken into account. The presented model of pollution prediction has been verified by way of real weather and air pollution data taken from the Airly sensor network. The dense and distributed network of Airly measurement devices enables access to current and archival data on air pollution, temperature, suspended particulate matter PM1.0, PM2.5, and PM10, CAQI levels, as well as atmospheric pressure and air humidity. In this investigation, PM2.5, and PM10, temperature and wind information, as well as external forecasts of temperature and wind for next 24h served as inputted data. Due to the specificity of the CNN type network, this data is transformed into tensors and then processed. This network consists of an input layer, an output layer, and many hidden layers. In the hidden layers, convolutional and pooling operations are performed. The output of this system is a vector containing 24 elements that contain prediction of PM10 concentration for the upcoming 24 hour period. Over 1000 models based on CNN methodology were tested during the study. During the research, several were selected out that give the best results, and then a comparison was made with the other models based on linear regression. The numerical tests carried out fully confirmed the positive properties of the presented method. These were carried out using real ‘big’ data. Models based on the CNN technique allow prediction of PM10 dust concentration with a much smaller mean square error than currently used methods based on linear regression. What's more, the use of neural networks increased Pearson's correlation coefficient (R²) by about 5 percent compared to the linear model. During the simulation, the R² coefficient was 0.92, 0.76, 0.75, 0.73, and 0.73 for 1st, 6th, 12th, 18th, and 24th hour of prediction respectively.

Keywords: air pollution prediction (forecasting), machine learning, regression task, convolution neural networks

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Authors: Tai Yuan Yu, Pei-Jen Wang

Abstract:

A simulation scheme of rotational motions for predictions of bump-type gas foil bearings operating at steady-state is proposed; and, the scheme is based on multi-physics coupling computer aided engineering packages modularized with computational fluid dynamic model and structure elasticity model to numerically solve the dynamic equation of motions of a hydrodynamic loaded shaft supported by an elastic bump foil. The bump foil is assumed to be modelled as infinite number of Hookean springs mounted on stiff wall. Hence, the top foil stiffness is constant on the periphery of the bearing housing. The hydrodynamic pressure generated by the air film lubrication transfers to the top foil and induces elastic deformation needed to be solved by a finite element method program, whereas the pressure profile applied on the top foil must be solved by a finite element method program based on Reynolds Equation in lubrication theory. As a result, the equation of motions for the bearing shaft are iteratively solved via coupling of the two finite element method programs simultaneously. In conclusion, the two-dimensional center trajectory of the shaft plus the deformation map on top foil at constant rotational speed are calculated for comparisons with the experimental results.

Keywords: computational fluid dynamics, fluid structure interaction multi-physics simulations, gas foil bearing, load capacity

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Authors: Muhammad Farooq Baig

Abstract:

Objective: The purpose of this study was to compare results obtained using a single fecal specimen for O&P examination, direct immunofluorescence assay (DFA), and two conventional staining methods. Design: Hundred and fifty children fecal specimens were collected and examined by each method. The O&P and the DFA were used as the reference method. Setting: The study was performed at the laboratory in the Basic Medical Science Institute JPMC Karachi. Patients or Other Participants: The fecal specimens were collected from children with a suspected Giardia lamblia infection. Main Outcome Measures: The amount of agreement and disagreement between methods.1) Presence of giardiasis in our population. 2) The sensitivity and specificity of each method. Results: There was 45(30%) positive 105 (70%) negative on DFA, 41 (27.4%) positive 109 (72.6%) negative on iodine and 34 (22.6%) positive 116(77.4%) on saline method. The sensitivity and specificity of DFA in comparision to iodine were 92.2%, 92.7% respectively. The sensitivity and specificity of DFA in comparisoin to saline method were 91.2%, 87.9% respectively. The sensitivity of iodine method and saline method in compariosn to DFA were 82.2%, 68.8% respectively. There is mark diffrence in sensitivity of DFA to conventional method. Conclusion: The study supported findings of other investigators who concluded that DFA method have the greater sensitivity. The immunologic methods were more efficient and quicker than the conventional O&P method.

Keywords: direct immunofluorescence assay (DFA), ova and parasite (O&P), Giardia lamblia, children, medical science

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Authors: N. A. Masevhe, M. Nemukula, S. S. Gololo, K. G. Kgosana

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Background and Study Significance: Legume seeds are important in agriculture as they are used for feed formulations due to their nutrient-dense, low-cost, and easy accessibility. Although they are important sources of energy, proteins, carbohydrates, vitamins, and minerals, they contain abundant quantities of anti-nutritive factors that reduce the bioavailability of nutrients, digestibility of proteins, and mineral absorption in livestock. However, the removal of these factors is too costly as it requires expensive state-of-the-art techniques such as high pressure and thermal processing. Basic Methodologies: The aim of the study was to investigate cost-effective methods that can be used to reduce the inherent phytates as putative antinutrients in the legume seeds. The seeds of Arachis hypogaea, Pisum sativum and Vigna radiata L. were subjected to the single processing methods viz raw seeds plus dehulling (R+D), soaking plus dehulling (S+D), ordinary cooking plus dehulling (C+D), infusion plus dehulling (I+D), autoclave plus dehulling (A+D), microwave plus dehulling (M+D) and five combined methods (S+I+D; S+A+D; I+M+D; S+C+D; S+M+D). All the processed seeds were dried, ground into powder, extracted, and analyzed on a microplate reader to determine the percentage of phytates per dry mass of the legume seeds. Phytic acid was used as a positive control, and one-way ANOVA was used to determine the significant differences between the means of the processing methods at a threshold of 0.05. Major Findings: The results of the processing methods showed the percentage yield ranges of 39.1-96%, 67.4-88.8%, and 70.2-93.8% for V. radiata, A. hypogaea and P. sativum, respectively. Though the raw seeds contained the highest contents of phytates that ranged between 0.508 and 0.527%, as expected, the R+D resulted in a slightly lower phytate percentage range of 0.469-0.485%, while other processing methods resulted in phytate contents that were below 0.35%. The M+D and S+M+D methods showed low phytate percentage ranges of 0.276-0.296% and 0.272-0.294%, respectively, where the lowest percentage yield was determined in S+M+D of P. sativum. Furthermore, these results were found to be significantly different (p<0.05). Though phytates cause micronutrient deficits as they chelate important minerals such as calcium, zinc, iron, and magnesium, their reduction may enhance nutrient bioavailability since they cannot be digested by the ruminants. Concluding Statement: Despite the nutritive aspects of the processed legume seeds, which are still in progress, the M+D and S+M+D methods, which significantly reduced the phytates in the investigated legume seeds, may be recommended to the local farmers and feed-producing industries so as to enhance animal health and production at an affordable cost.

Keywords: anti-nutritive factors, extraction, legume seeds, phytate

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Authors: Lakshya Bhat, Anubhav Shrivastava, Shiva Rudraswamy

Abstract:

There has been a formidable interest in the area of Distributed Generation in recent times. A wide number of loads are addressed by Distributed Generators and have better efficiency too. The major disadvantage in Distributed Generation is voltage control- is highlighted in this paper. The paper addresses voltage control at buses in IEEE 14 Bus system by regulating reactive power. An analysis is carried out by selecting the most optimum location in placing the Distributed Generators through load flow analysis and seeing where the voltage profile rises. MATLAB programming is used for simulation of voltage profile in the respective buses after introduction of DG’s. A tolerance limit of +/-5% of the base value has to be maintained. To maintain the tolerance limit, 3 methods are used. Sensitivity analysis of 3 methods for voltage control is carried out to determine the priority among the methods.

Keywords: distributed generators, distributed system, reactive power, voltage control, sensitivity analysis

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Authors: Yesim Özogul, Fethiye Takadaş, Mustafa Durmus, Yılmaz Ucar, Ali Rıza Köşker, Gulsun Özyurt, Fatih Özogul

Abstract:

It has been well documented that polyunsaturated fatty acids (PUFAs), especially eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) have beneficial effects on health, regarding prevention of cardiovascular diseases, cancer and autoimmune disorders, development the brain and retina and treatment of major depressive disorder etc. Thus, an adequate intake of omega PUFA is essential and generally marine fish are the richest sources of PUFA in human diet. Thus, this study was conducted to evaluate the efficiency of different extraction methods (Bligh and Dyer, soxhlet, microwave and ultrasonics) on the fat content and fatty acid profiles of marine fish species (Mullus babatus, Upeneus moluccensis, Mullus surmuletus, Anguilla anguilla, Pagellus erythrinus and Saurida undosquamis). Fish species were caught by trawl in Mediterranean Sea and immediately iced. After that, fish were transported to laboratory in ice and stored at -18oC in a freezer until the day of analyses. After extracting lipid from fish by different methods, lipid samples were converted to their constituent fatty acid methyl esters. The fatty acid composition was analysed by a GC Clarus 500 with an autosampler (Perkin Elmer, Shelton, CT, USA) equipped with a flame ionization detector and a fused silica capillary SGE column (30 m x 0.32 mm ID x 0.25 mm BP20 0.25 UM, USA). The results showed that there were significant differences (P < 0.05) in fatty acids of all species and also extraction methods affected fat contents and fatty acid profiles of fish species.

Keywords: extraction methods, fatty acids, marine fish, PUFA

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